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Classe IPC
G06F 17/30 - Recherche documentaire; Structures de bases de données à cet effet 5 355
H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole 4 101
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En Instance 3 757
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1.

INTELLIGENT NEAR-FIELD ADVERTISEMENT WITH OPTIMIZATION

      
Numéro d'application 18537443
Statut En instance
Date de dépôt 2023-12-12
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s) Shah, Shrey

Abrégé

In non-limiting examples of the present disclosure, systems, methods, and devices for intelligent advertising with optimization. A first device may determine a scenario for completion with a second device. The first device may receive device signals associated with the scenario. The first device may analyze the device signals based on the scenario with a rules engine. The first device may determine whether the second device is ready to participate in the scenario. In response to determining that the second device is ready to participate in the scenario, the first device may transmit an advertisement or listen for an advertisement from the second device.

Classes IPC  ?

  • H04L 67/147 - Méthodes de signalisation ou messages fournissant des extensions aux protocoles définis par la normalisation
  • G06N 5/025 - Extraction de règles à partir de données

2.

SCALABLE CONTROLLER FOR MANAGING DATA STORAGES

      
Numéro d'application 17950955
Statut En instance
Date de dépôt 2022-09-22
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Oshins, Jacob Kappeler
  • Angepat, Hari Daas
  • Yuan, Yi
  • Makhervaks, Vadim

Abrégé

Embodiments of the present disclosure include systems and methods for providing a scalable controller for managing data storages. A system includes a non-volatile memory controller comprising a set of data queues and a set of administrative queues. The system also includes a set of physical storages communicatively coupled to the non-volatile memory controller. A set of logical storages are created from the set of physical storages. A primary non-volatile memory controller is created from the non-volatile memory controller. The primary non-volatile memory controller comprising an administrative queue in the set of administrative queues, a first subset of the set of data queues, and a first subset of the set of logical storages. An extended non-volatile memory controller is created from the non-volatile memory controller. The extended non-volatile memory controller comprising a second subset of the set of data queues and a second subset of the set of logical storages.

Classes IPC  ?

  • G06F 3/06 - Entrée numérique à partir de, ou sortie numérique vers des supports d'enregistrement

3.

Generating A Gallery View From An Area View

      
Numéro d'application 17950985
Statut En instance
Date de dépôt 2022-09-22
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Master Ben-Dor, Karen
  • Zychlinski, Eshchar
  • Yagev, Stav
  • Smolin, Yoni
  • Halaly, Raz
  • Diamant, Adi
  • Leichter, Ido
  • Shlomi, Tamir

Abrégé

Techniques for generating a gallery view of tiles for in-area participants who are participating in an online meeting are disclosed. A video stream is accessed, where this stream includes an area view of an area in which an in-area participant is located. This area view comprises pixels representative of the area and pixels representative of the in-area participant. The pixels representative of the in-area participant are identified. A field of view of the in-area participant is generated. A tile of the in-area participant is generated based on the field of view. This tile is then displayed while the area view is not displayed.

Classes IPC  ?

  • G06T 5/00 - Amélioration ou restauration d'image
  • G06T 3/40 - Changement d'échelle d'une image entière ou d'une partie d'image
  • G06T 5/20 - Amélioration ou restauration d'image en utilisant des opérateurs locaux
  • G06T 11/00 - Génération d'images bidimensionnelles [2D]
  • G06V 10/26 - Segmentation de formes dans le champ d’image; Découpage ou fusion d’éléments d’image visant à établir la région de motif, p.ex. techniques de regroupement; Détection d’occlusion
  • G06V 20/40 - RECONNAISSANCE OU COMPRÉHENSION D’IMAGES OU DE VIDÉOS Éléments spécifiques à la scène dans le contenu vidéo

4.

SYSTEMS AND METHODS FOR THERMAL SYSTEM MANAGEMENT

      
Numéro d'application 18529591
Statut En instance
Date de dépôt 2023-12-05
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Rintamaeki, Mika Juhani
  • Nielsen, Gregory Allen
  • Venkatachalam, Rajagopal K.
  • Justin, Ajit
  • Cantu De La Garza, Francisco

Abrégé

A method of thermal and power control in a computing device includes, at the computing device, initializing a thermal module of the computing device, receiving data at the thermal module from a first component assigned to an interface of the thermal module, and sending an output to a second component from the thermal module based on the data. Initializing the thermal module includes detecting a presence of a plurality of potential components of the computing device; querying each of the plurality of potential components to determine capabilities of each component; in response to the querying, for each of at least a subset of the plurality of potential components receiving identification information for the component and, based on the received identification information, configuring one or more interfaces of the plurality of predefined interfaces of the thermal module to establish communication with the sub set of components.

Classes IPC  ?

  • G06F 1/3234 - Gestion de l’alimentation, c. à d. passage en mode d’économie d’énergie amorcé par événements Économie d’énergie caractérisée par l'action entreprise
  • G05B 17/02 - Systèmes impliquant l'usage de modèles ou de simulateurs desdits systèmes électriques
  • G06F 1/20 - Moyens de refroidissement
  • G06F 1/3212 - Surveillance du niveau de charge de la batterie, p.ex. un mode d’économie d’énergie étant activé lorsque la tension de la batterie descend sous un certain niveau

5.

RETRACTABLE CONNECTOR

      
Numéro d'application 17936276
Statut En instance
Date de dépôt 2022-09-28
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Nguyen, Minh Cao
  • Allaway, David Scott
  • Morena, Gianna Marie

Abrégé

A connector includes a housing including a plug opening and a cable opening. A cable extends through the cable opening away from the housing. An electronic plug is connected to the cable within the housing and extends through the plug opening away from the housing. The electronic plug is selectively moveable relative to the housing between an extended position and a retracted position when a pulling force is applied to the cable. A bias mechanism biases the electronic plug to the extended position.

Classes IPC  ?

  • H01R 13/60 - Moyens pour supporter les pièces de couplage non engagées
  • H01R 13/62 - Moyens pour faciliter l'engagement ou la séparation des pièces de couplage ou pour les maintenir engagées
  • H01R 13/635 - Moyens additionnels pour faciliter l'engagement ou la séparation des pièces de couplage, p.ex. moyens pour aligner ou guider, leviers, pression de gaz pour la séparation uniquement par une pression mécanique, p.ex. par la force d'un ressort
  • H01R 24/28 - Pièces de couplage portant des broches, des lames ou des contacts analogues, assujetties uniquement à un fil ou un câble

6.

SYSTEMS AND METHODS FOR ADJUSTING PRESSURE IN IMMERSION-COOLED DATACENTERS

      
Numéro d'application 17953834
Statut En instance
Date de dépôt 2022-09-27
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Nasr Azadani, Ehsan
  • Ramakrishnan, Bharath
  • Keehn, Nicholas Andrew
  • Alissa, Husam Atallah
  • Nagimov, Ruslan
  • Peterson, Eric C.

Abrégé

A thermal management system includes a high-pressure (HP) container, a low-pressure (LP) container in fluid communication with the HP container and having a fluid pressure less than the HP container, and a two-phase working fluid partially in the HP container and partially in the LP container. The two-phase working fluid has a vapor phase and a liquid phase. A pump is configured to move the working fluid through the system, and a condenser is configured to condense the vapor phase of the working fluid into the liquid phase.

Classes IPC  ?

7.

FARBRICATION METHOD

      
Numéro d'application 17753581
Statut En instance
Date de dépôt 2019-09-10
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Aseev, Pavel
  • Caroff-Gaonac'H, Philippe
  • Kouwenhoven, Leonardus Petrus

Abrégé

A fabrication method comprising: forming a mask of an amorphous material over a crystalline surface of a substrate, the mask having a pattern of openings defining areas of an active region in which one or more components of one or more active devices are to be formed, the mask further defining a non-active region in which no active devices are to be formed; and forming a deposition material through the mask by an epitaxial growth process. The deposition material thus forms in the openings of the active region. The pattern of openings through the mask further comprises one or more reservoirs formed in the non-active region, each of the reservoirs being connected by the pattern of openings in the mask to at least one of the areas in the active region, and the deposition material forming in the reservoirs as part of the epitaxial growth.

Classes IPC  ?

  • H10N 60/01 - Fabrication ou traitement
  • C30B 25/04 - Dépôt suivant une configuration déterminée, p.ex. en utilisant des masques
  • C30B 29/40 - Composés AIII BV
  • C30B 29/60 - Monocristaux ou matériaux polycristallins homogènes de structure déterminée caractérisés par leurs matériaux ou par leur forme caractérisés par la forme
  • H10N 69/00 - Dispositifs intégrés, ou ensembles de plusieurs dispositifs, comportant au moins un élément supraconducteur couvert par le groupe

8.

HIGH LATENCY QUERY OPTIMIZATION SYSTEM

      
Numéro d'application 18067170
Statut En instance
Date de dépôt 2022-12-16
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s) Netes, Nir

Abrégé

The described technology provides high latency query optimization method including receiving a data request from a client, the data request directed to data stored in a plurality of data shards, determining a set of operating parameters of the data shards for retrieving data from the plurality of shards, determining a chunking factor based on the set of operating parameters, dividing the data request into a plurality of API requests based on the chunking factor, each of the API requests directed to a portion of the plurality of data shards, and communicating the plurality of API requests in parallel to a source API configured to perform data queries on the plurality of data shards.

Classes IPC  ?

  • G06F 16/2453 - Optimisation des requêtes
  • G06F 9/54 - Communication interprogramme
  • G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuées; Architectures de systèmes de bases de données distribuées à cet effet

9.

VERIFIABLE ATTRIBUTE MAPS

      
Numéro d'application 17934730
Statut En instance
Date de dépôt 2022-09-23
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Venkatesan, Ramarathnam
  • Setty, Srinath T. V.
  • Chandran, Nishanth
  • Antonopoulos, Panagiotis

Abrégé

Verifiable attribute maps that maintain references to identities and attribute information associated with the identities are disclosed. A verifiable attribute map is maintained by a ledger database that provides tamper-resistant/evident capabilities for tables (comprising the map) thereof. For instance, when a materialized view of the database is generated, the database provides a digest representative of a state thereof to computing devices that access the map for the attribute information. When the database receives a request from a device to access the map, the digest is received along therewith. The database is validated based on the digest to determine whether the database has been tampered with since the provision of the digest. Responsive to a successful validation, the database provides access in accordance with the request. When attribute information in the map is updated, the database subsequently generates a new digest, which is provided to the computing device.

Classes IPC  ?

  • G06F 21/62 - Protection de l’accès à des données via une plate-forme, p.ex. par clés ou règles de contrôle de l’accès
  • H04L 9/00 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité

10.

INTELLIGENT CONTENT RECOMMENDATIONS BASED ON SELECTIONS OF CURATED REVIEW RESPONSES

      
Numéro d'application 17951068
Statut En instance
Date de dépôt 2022-09-22
Date de la première publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Taylor, Eric Warner
  • Buckley, Aaron John Mayer
  • Merriam, Jesse Dylan

Abrégé

The techniques disclosed herein provide recommendations of content based on user selections of curated review responses. A system can provide a set of curated response candidates and a related question to users providing a review of a product. The set of curated response candidates are selected based on a category that is determined by one or more factors. For example, if a user is to provide a review on a video game, the category can be based on aspects of the video game, such as visual features, game play features, etc. A user can respond to the question by selecting at least one of the curated response candidates. The system can then analyze a data structure that associates the selected response to one or more characteristics to determine characteristics that are preferred by the user. The system can then use the characteristics to recommend other content.

Classes IPC  ?

  • G06Q 30/02 - Marketing; Estimation ou détermination des prix; Collecte de fonds

11.

DIRECT SWAP CACHING WITH ZERO LINE OPTIMIZATIONS

      
Numéro d'application 18503869
Statut En instance
Date de dépôt 2023-11-07
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Agarwal, Ishwar
  • Chrysos, George
  • Rosell Martinez, Oscar
  • Bak, Yevgeniy

Abrégé

Systems and methods related to direct swap caching with zero line optimizations are described. A method for managing a system having a near memory and a far memory comprises receiving a request from a requestor to read a block of data that is either stored in the near memory or the far memory. The method includes analyzing a metadata portion associated with the block of data, the metadata portion comprising: both (1) information concerning whether the near memory contains the block of data or whether the far memory contains the block of data and (2) information concerning whether a data portion associated with the block of data is all zeros. The method further includes instead of retrieving the data portion from the far memory, synthesizing the data portion corresponding to the block of data to generate a synthesized data portion and transmitting the synthesized data portion to the requestor.

Classes IPC  ?

  • G06F 9/38 - Exécution simultanée d'instructions
  • G06F 9/445 - Chargement ou démarrage de programme
  • G06F 9/50 - Allocation de ressources, p.ex. de l'unité centrale de traitement [UCT]
  • G06F 12/0815 - Protocoles de cohérence de mémoire cache

12.

ANALYSIS OF SPREADSHEET TABLE IN RESPONSE TO USER INPUT

      
Numéro d'application 18263285
Statut En instance
Date de dépôt 2022-02-03
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Hou, Zhitao
  • Zhang, Haidong
  • Wang, Yun
  • Zhang, Dongmei
  • Lou, Jian-Guang

Abrégé

According to implementations of the present disclosure, there is proposed a solution for analyzing a data table in response to a user input. In this solution, a user input in a cell of a data table is determined. The data table comprises a plurality of cells arranged in rows and columns. An analysis operation for the data table is determined based on semantics of the data table and the user input, the analysis operation corresponding to the user input. Further, a result of the analysis operation is presented in a region of the data table related to the cell. In this way, grid characteristics of the data table can be utilized to provide the result of the analysis operation as desired by a user and simple, efficient and user-friendly data analysis can be facilitated.

Classes IPC  ?

  • G06F 40/18 - Traitement de texte Édition, p.ex. insertion ou suppression utilisant des lignes réglées de tableurs
  • G06F 40/30 - Analyse sémantique

13.

GENERATING AND USING A SEMANTIC INDEX

      
Numéro d'application 17953048
Statut En instance
Date de dépôt 2022-09-26
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Sommerlade, Eric Chris Wolfgang
  • Pradeep, Vivek
  • Bathiche, Steven N.
  • Luquetta-Fish, Nathan

Abrégé

Methods and systems for generating and using a semantic index are provided. In some examples, content data is received. The content data includes a plurality of subsets of content data. Each of the plurality of subsets of content data are labelled, based on a semantic context corresponding to the content data. The plurality of subsets of content data and their corresponding labels are stored. The plurality of subsets of content data are grouped, based on their labels, thereby generating one or more groups of subsets of content data. Further, a computing device is adapted to perform an action, based on the one or more groups of subsets of content data.

Classes IPC  ?

  • G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
  • G06F 16/22 - Indexation; Structures de données à cet effet; Structures de stockage
  • G06F 40/30 - Analyse sémantique

14.

MODELLING CAUSATION IN MACHINE LEARNING

      
Numéro d'application 17936338
Statut En instance
Date de dépôt 2022-09-28
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Ma, Chao
  • Zhang, Cheng
  • Ashman, Matthew
  • Defante, Marife
  • Fassio, Karen
  • Jennings, Joel
  • Hilmkil, Agrin

Abrégé

A method comprising: sampling a first causal graph from a first graph distribution modelling causation between variables in a feature vector, and sampling a second causal graph from a second graph distribution modelling presence of possible confounders, a confounder being an unobserved cause of both of two variables. The method further comprises: identifying a parent variable which is a cause of a selected variable according to the first causal graph, and which together with the selected variable forms a confounded pair having a respective confounder being a cause of both according to the second causal graph. A machine learning model encodes the parent to give a first embedding, and encodes information on the confounded pair give a second embedding. The embeddings are combined and then decoded to give a reconstructed value. This mechanism may be used in training the model or in treatment effect estimation.

Classes IPC  ?

  • G06N 3/08 - Méthodes d'apprentissage
  • G06N 3/0455 - Réseaux auto-encodeurs; Réseaux encodeurs-décodeurs

15.

FEW-SHOT CLASSIFIER EXAMPLE EXTRACTION

      
Numéro d'application 18065617
Statut En instance
Date de dépôt 2022-12-13
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Massiceti, Daniela
  • Basu, Samyadeep
  • Stanley, Megan Jane

Abrégé

In various examples there is a computer-implemented method comprising accessing a pool of examples. The method obtains a query set comprising a plurality of held out examples in a plurality of classes. For each example in the pool, the method assigns a weight to the example and initializes the weight using a default or random value. The method accesses a constrained optimization problem. The constrained optimization is solved using a projected gradient ascent or descent, the solving resulting in optimal weights resulting in an optimal performance of a few-shot classifier on the query set, where the few-shot classifier is trained using the examples from the pool weighted by the optimal weights. The method selects, using the optimal weights, an example per class from the pool, and stores the selected examples.

Classes IPC  ?

  • G06F 17/11 - Opérations mathématiques complexes pour la résolution d'équations
  • G06V 10/25 - Détermination d’une région d’intérêt [ROI] ou d’un volume d’intérêt [VOI]
  • G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p.ex. des objets vidéo

16.

SYSTEM AND METHOD FOR INVERSE SUMMARIZATION OF MEDICAL RECORDS WITH DATA AUGMENTATION AND KNOWLEDGE DISTILLATION

      
Numéro d'application 17951742
Statut En instance
Date de dépôt 2022-09-23
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing LLC (USA)
Inventeur(s) Fu, Zhongkai

Abrégé

A method, computer program product, and computing system for generating a first synthetic dataset including a synthetic transcription and a corresponding natural dictation record using a first machine learning model trained to generate transcriptions from medical records. A second synthetic dataset including a synthetic medical record and a corresponding natural transcription is generated using a second machine learning model trained to generate medical records from transcriptions. The first synthetic dataset and the second synthetic dataset are combined with a natural dataset into a synthetic training dataset.

Classes IPC  ?

  • G16H 15/00 - TIC spécialement adaptées aux rapports médicaux, p.ex. leur création ou leur transmission
  • G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques

17.

USING UNSUPERVISED MACHINE LEARNING TO IDENTIFY ATTRIBUTE VALUES AS RELATED TO AN INPUT

      
Numéro d'application 17935060
Statut En instance
Date de dépôt 2022-09-23
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Wu, Liwei
  • Ni, Lichao
  • Guerrero, Mikaela Makalinao
  • Li, Yanen

Abrégé

Technologies for skill taxonomy management are described. Embodiments include extracting an input text from an online system and applying an unsupervised generative text machine learning model to the input text. The text generator generates a set of sentences based on a job title included in the input text. One or more skills are extracted from the set of sentences. The extracted one or more skills correspond to one or more skills in a skill taxonomy. A frequency distribution is generated over the extracted one or more skills. The one or more skills are ranked based on the frequency distribution. Based on the ranking, a subset of the extracted one or more skills is generated. The subset of the extracted one or more skills is provided to a downstream operation, process, or service of the online system.

Classes IPC  ?

18.

METHOD AND SYSTEM OF INTELLIGENTLY GENERATING A TITLE FOR A GROUP OF DOCUMENTS

      
Numéro d'application 17950475
Statut En instance
Date de dépôt 2022-09-22
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s) Mcanallen, Julia S

Abrégé

A system and method automatically generating a title for a cluster of documents includes accessing a plurality of documents that have been categorized as belonging to a document cluster and providing the plurality of documents as an input to a trained title generating machine-learning (ML) model. The trained title generating ML model is trained for generating a title for a document and provides a titles for each of the plurality of documents. An embedding is created for the generated titles and then an embedding is generated for the document cluster. A similarity between the embeddings for the titles and embedding for the document cluster is measured to identify titles that are more similar to the embedding for the document cluster and based on the similarity one or more titles are selected as title candidates for the document cluster and provided as an output.

Classes IPC  ?

  • G06F 16/16 - Opérations sur les fichiers ou les dossiers, p.ex. détails des interfaces utilisateur spécialement adaptées aux systèmes de fichiers
  • G06F 16/35 - Groupement; Classement

19.

SCHEMA AUGMENTATION SYSTEM FOR EXPLORATORY RESEARCH

      
Numéro d'application 18531333
Statut En instance
Date de dépôt 2023-12-06
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Ramos, Gonzalo A.
  • Suh, Jin A
  • Meek, Christopher Alan
  • Ng, Shiqian Rachel
  • Rachatasumrit, Napol

Abrégé

In examples, a schema augmentation system for exploratory research leverages intelligence from a machine learning model to augment such tasks by leveraging intelligence derived from machine learning capabilities. Augmenting tasks include schematization of content, such as information units and groupings of information units. Based on the schematization of such content, semantic proximities for information units are determined. The semantic proximities may be used to identify and present potentially relevant information units, for example to accelerate the exploratory research task at hand. As such, users engaged in consumption of heterogenous content (e.g., across client applications and/or content sources), may receive machine-augmented support to find potential information units. To optimize machine training, user input may be received, such that the system may intelligently augment the user's exploratory research task based on the semantic coherence of the content processed from information units and associated user behavior.

Classes IPC  ?

  • G06N 5/022 - Ingénierie de la connaissance; Acquisition de la connaissance
  • G06F 16/904 - Navigation; Visualisation à cet effet
  • G06F 40/103 - Mise en forme, c. à d. modification de l’apparence des documents
  • G06F 40/30 - Analyse sémantique
  • G06N 20/00 - Apprentissage automatique

20.

REVERSE PROXY SERVERS FOR IMPLEMENTING APPLICATION LAYER-BASED AND TRANSPORT LAYER-BASED SECURITY RULES

      
Numéro d'application 18488798
Statut En instance
Date de dépôt 2023-10-17
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Lewin, Guy
  • Khait, Vitaly
  • Haber, Yossi

Abrégé

The implementation of application layer-based and transport-layer based security rules via a reverse proxy server chain is described. Each reverse proxy server in the chain is configured to perform a particular function with respect to client messages intended for a destination server and/or convey contextual information pertaining to the messages to a subsequent reverse proxy server in the chain. For instance, a first reverse proxy server in the chain is configured to include client-specific metadata in the transport layer of the message. A second reverse proxy server in the chain enforces transport layer-based policy rules based on the metadata. This enables the second reverse proxy server to manage transport layer connections on a client-by-client basis, thereby enabling the second reverse proxy server to block unauthorized clients, while maintaining the transport layer connections for authorized clients. A third reverse proxy server in the chain enforces application layer-based policy rules.

Classes IPC  ?

  • H04L 9/40 - Protocoles réseaux de sécurité

21.

OLIGONUCLEOTIDE ASSEMBLY USING ELECTRICALLY CONTROLLED HYBRIDIZATION

      
Numéro d'application 18521106
Statut En instance
Date de dépôt 2023-11-28
Date de la première publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Chen, Yuan-Jyue
  • Nguyen, Bichlien
  • Smith, Jake
  • Strauss, Karin

Abrégé

Electrically controlled hybridization is used to selectively assemble oligonucleotides on the surface of a microelectrode array. Controlled activation of individual electrodes in the microelectrode array attracts oligonucleotides in solution to specific regions of the array where they hybridize to other oligonucleotides anchored on the array. The oligonucleotides that hybridize may provide locations for subsequent oligonucleotides to hybridize. The active electrodes and the oligonucleotides in solution may be varied during each round of synthesis. This allows for multiple oligonucleotides each with different and specific sequences to be created in parallel. This is accomplished without the use of phosphoramidite chemical synthesis or template-independent DNA polymerase enzymatic synthesis. Oligonucleotides created with these techniques may be used to encode digital data. Fully assembled oligonucleotides may be separated from the array and sequenced, stored, or otherwise processed.

Classes IPC  ?

  • C12N 15/10 - Procédés pour l'isolement, la préparation ou la purification d'ADN ou d'ARN
  • B01L 3/00 - Récipients ou ustensiles pour laboratoires, p.ex. verrerie de laboratoire; Compte-gouttes
  • C12Q 1/6874 - Méthodes de séquençage faisant intervenir des réseaux d’acides nucléiques, p.ex. séquençage par hybridation [SBH]
  • G06N 3/123 - Informatique à ADN
  • G11C 13/02 - Mémoires numériques caractérisées par l'utilisation d'éléments d'emmagasinage non couverts par les groupes , ou utilisant des éléments dont le fonctionnement dépend d'un changement chimique
  • G16B 50/40 - Cryptage de données génétiques

22.

PEER VIRTUAL MACHINE MONITORING AND AUTO-HEALING SYSTEM

      
Numéro d'application 17950298
Statut En instance
Date de dépôt 2022-09-22
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Mutha, Akshay Navneetlal
  • Rodriguez, Eric Phillip
  • Hao, Peilin

Abrégé

Systems and methods for monitoring health of virtual machines (VMs) include determining a leader virtual machine (VM) count for a group of VM nodes hosted on a plurality of computing devices; selecting a number of the VM nodes of the group to serve as leader VMs for the group, the number of the VM nodes selected corresponding to the leader VM count; and periodically performing a peer VM monitoring process. The peer VM monitoring process includes periodically storing health information for each of the VM nodes of the group in a data store; periodically accessing the health information of each of the VM nodes to identify sick VMs using each of the leader VMs, respectively; and automatically performing a healing process on the sick VMs to improve a performance of the sick VMs.

Classes IPC  ?

  • G06F 9/455 - Dispositions pour exécuter des programmes spécifiques Émulation; Interprétation; Simulation de logiciel, p.ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation

23.

HARDWARE SOLVER ARCHITECTURE

      
Numéro d'application 18264260
Statut En instance
Date de dépôt 2022-01-28
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Parmigiani, Francesca
  • Gkantsidis, Christos
  • Haller, István
  • Ballani, Hitesh
  • Rowstron, Antony Ian Taylor
  • Rybalchenko, Andrey

Abrégé

A system for estimating values of a vector of variables that optimize a function comprising a weighted sum of interactions between the variables; the system comprising a plurality of parallel hardware channels, each arranged to model a contribution of a respective variable to the function, each channel comprising: a signal generator configured to generate a signal modelling a value of the respective variable; a splitter arranged to supply the signal to each of the channels; interaction logic configured to multiply the vector of signals by a vector of weights modelling an interaction between the respective variable and the vector of variables, thereby generating a feedback signal representing the contribution of the respective variable; and a feedback path to return the feedback signal to the signal generator configured to adapt the signal in dependence on the feedback signal, wherein each channel is implemented only using optical components and/or analogue electronic components.

Classes IPC  ?

  • G06F 17/11 - Opérations mathématiques complexes pour la résolution d'équations
  • G06F 17/16 - Calcul de matrice ou de vecteur

24.

STOCHASTICITY MITIGATION IN DEPLOYED AI AGENTS

      
Numéro d'application US2023030882
Numéro de publication 2024/063897
Statut Délivré - en vigueur
Date de dépôt 2023-08-23
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Maitra, Kingsuk
  • Bryant, Brendan Lee
  • Premoe, Chris Allen
  • Anderson, Kence

Abrégé

The techniques disclosed herein mitigate stochasticity when controlling a mechanical system with artificial intelligence (AI) agents. In some configurations, AI agents are created using data generated by a machine learning model. Stochasticity is segmented temporally into near term and long term, and different strategies are used to address stochasticity in the different timeframes. For example, long term stochasticity may be addressed with changes to the reward function used to train the model. Short term stochasticity may be addressed by applying a margin to the output of an AI agent. Example margins include window averaging, clamps, and statistical process control bounds. In one configuration, AI agents are regression brains that are generated from setpoints inferred by the model from environmental states. The limitations inherent to fitting a regression line to this data may result in some predicted setpoints being outside of an allowed range.

Classes IPC  ?

  • G06N 3/006 - Vie artificielle, c. à d. agencements informatiques simulant la vie fondés sur des formes de vie individuelles ou collectives simulées et virtuelles, p.ex. simulations sociales ou optimisation par essaims particulaires [PSO]
  • G06N 3/092 - Apprentissage par renforcement

25.

INTEGRATING MODEL REUSE WITH MODEL RETRAINING FOR VIDEO ANALYTICS

      
Numéro d'application US2023028308
Numéro de publication 2024/063851
Statut Délivré - en vigueur
Date de dépôt 2023-07-21
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Ananthanarayanan, Ganesh
  • Shu, Yuanchao
  • Bahl, Paramvir
  • Hsieh, Tsuwang

Abrégé

Systems and methods are provided for reusing and retraining an image recognition model for video analytics. The image recognition model is used for inferring a. frame of video data, that is captured at edge devices. The edge devices periodically or under predetermined conditions transmits a captured frame of video data, to perform inferencing. The disclosed technology is directed to select an image recognition model from a model store for reusing or for retraining. A model selector uses a. gating network model to determine ranked candidate models for validation. The validation includes iterations of retraining the image recognition model and stopping the iteration when a rate of improving accuracy by retraining becomes smaller than the previous iteration step. Retraining a model includes generating reference data using a teacher model and retraining the model using the reference data. Integrating reuse and retraining of models enables improvement in accuracy and efficiency.

Classes IPC  ?

  • G06V 10/774 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p.ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]; Séparation aveugle de source méthodes de Bootstrap, p.ex. "bagging” ou “boosting”
  • G06V 10/776 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p.ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]; Séparation aveugle de source Évaluation des performances
  • G06V 10/778 - Apprentissage de profils actif, p.ex. apprentissage en ligne des caractéristiques d’images ou de vidéos
  • G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
  • G06V 10/80 - Fusion, c. à d. combinaison des données de diverses sources au niveau du capteur, du prétraitement, de l’extraction des caractéristiques ou de la classification
  • G06V 10/70 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique

26.

DISTORTION CORRECTION VIA ANALYTICAL PROJECTION

      
Numéro d'application US2023027957
Numéro de publication 2024/063842
Statut Délivré - en vigueur
Date de dépôt 2023-07-18
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s) Powell, Karlton David

Abrégé

A method for processing a stream of input images is provided. The method includes receiving a stream of input images, and applying a digital effect to the stream of input images. The digital effect is one or more from the group of: a pan, a tilt, or a zoom, of the stream of input images. The method further includes selecting an analytical projection type, from a plurality of analytical projection types, that maps pixels of the input stream of images to projected pixels of a modified stream of images, generating the modified stream of images, using the selected analytical projection type, thereby correcting a geometric distortion within the stream of input images, while applying the digital effect, and displaying the modified stream of images.

Classes IPC  ?

  • G06T 3/00 - Transformation géométrique de l'image dans le plan de l'image
  • G06T 5/00 - Amélioration ou restauration d'image
  • H04N 23/698 - Commande des caméras ou des modules de caméras pour obtenir un champ de vision élargi, p. ex. pour la capture d'images panoramiques

27.

CORRECTING IMAGERY WITH DIFFERENTIAL APPLIED SCALARS

      
Numéro d'application US2023027955
Numéro de publication 2024/063841
Statut Délivré - en vigueur
Date de dépôt 2023-07-18
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Hershey, Kyle William
  • Piecuch, Scott Robert
  • Zheng, Ying

Abrégé

Disclosed is the differential application of scalars to compensate pixel degradation. Input image data is associated with a commanded luminance at each of a plurality of pixels. A degradation value is determined for each pixel. Based on the degradation value, an elevated drive current is determined to produce commanded luminance at the pixel. A required scalar is determined for each pixel to hold the elevated drive current from exceeding a drive current threshold. An applied scalar for each pixel is determined for each pixel to be applied to the elevated drive current. For at least some pixels, the applied scalar for a first pixel is based at least on [1] the required scalar of a second pixel and [2] a spatial relationship between the first pixel and the second pixel. Applied scalars are then used to output corrected imagery.

Classes IPC  ?

  • G09G 3/3208 - Dispositions ou circuits de commande présentant un intérêt uniquement pour l'affichage utilisant des moyens de visualisation autres que les tubes à rayons cathodiques pour la présentation d'un ensemble de plusieurs caractères, p.ex. d'une page, en composant l'ensemble par combinaison d'éléments individuels disposés en matrice utilisant des sources lumineuses commandées utilisant des panneaux électroluminescents semi-conducteurs, p.ex. utilisant des diodes électroluminescentes [LED] organiques, p.ex. utilisant des diodes électroluminescentes organiques [OLED]
  • G09G 3/20 - Dispositions ou circuits de commande présentant un intérêt uniquement pour l'affichage utilisant des moyens de visualisation autres que les tubes à rayons cathodiques pour la présentation d'un ensemble de plusieurs caractères, p.ex. d'une page, en composant l'ensemble par combinaison d'éléments individuels disposés en matrice

28.

HIGH LATENCY QUERY OPTIMIZATION SYSTEM

      
Numéro d'application US2023030987
Numéro de publication 2024/063902
Statut Délivré - en vigueur
Date de dépôt 2023-08-24
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s) Netes, Nir

Abrégé

The described technology provides high latency query optimization method including receiving a data request from a client, the data request directed to data stored in a plurality of data shards, determining a set of operating parameters of the data shards for retrieving data from the plurality of shards, determining a chunking factor based on the set of operating parameters, dividing the data request into a plurality of API requests based on the chunking factor, each of the API requests directed to a portion of the plurality of data shards, and communicating the plurality of API requests in parallel to a source API configured to perform data queries on the plurality of data shards.

Classes IPC  ?

29.

VERIFIABLE ATTRIBUTE MAPS

      
Numéro d'application US2023030988
Numéro de publication 2024/063903
Statut Délivré - en vigueur
Date de dépôt 2023-08-24
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Venkatesan, Ramarathnam
  • Setty, Srinath T. V.
  • Chandran, Nishanth
  • Antonopoulos, Panagiotis

Abrégé

Verifiable attribute maps that maintain references to identities and attribute information associated with the identities are disclosed. A verifiable attribute map is maintained by a ledger database that provides tamper-resistant/evident capabilities for tables (comprising the map) thereof. For instance, when a materialized view of the database is generated, the database provides a digest representative of a state thereof to computing devices that access the map for the attribute information. When the database receives a request from a device to access the map, the digest is received along therewith. The database is validated based on the digest to determine whether the database has been tampered with since the provision of the digest. Responsive to a successful validation, the database provides access in accordance with the request. When attribute information in the map is updated, the database subsequently generates a new digest, which is provided to the computing device.

Classes IPC  ?

  • G06F 21/62 - Protection de l’accès à des données via une plate-forme, p.ex. par clés ou règles de contrôle de l’accès
  • G06F 21/64 - Protection de l’intégrité des données, p.ex. par sommes de contrôle, certificats ou signatures
  • H04L 9/00 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité

30.

MULTI-PLATFORM PROCESS SERVICE

      
Numéro d'application US2023030753
Numéro de publication 2024/063888
Statut Délivré - en vigueur
Date de dépôt 2023-08-22
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s) Gilman, Jonathan Andrew

Abrégé

Execution of a process using a select platform-specific process application is provided, including identifying, from a set of received inputs, a collection of selection input parameter values uniquely associated in memory with a select platform-specific process application among different platform-specific process applications configured to implement a process of a process type, identifying a process population template associated in memory with the select platform-specific process application, the process population template identifying data input fields accepted as inputs to the select platform-specific process application, receiving, from a uniform user interface, a set of user inputs, and executing the process population template. The executing includes modifying the set of user inputs to generate modified inputs of a form consistent with the data input fields accepted as inputs to the select platform-specific process application and executing the select platform-specific process application based on the modified inputs.

Classes IPC  ?

  • G06F 9/54 - Communication interprogramme
  • G06F 8/38 - Création ou génération de code source pour la mise en œuvre d'interfaces utilisateur
  • G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur

31.

FEW-SHOT CLASSIFIER EXAMPLE EXTRACTION

      
Numéro d'application US2023030994
Numéro de publication 2024/063905
Statut Délivré - en vigueur
Date de dépôt 2023-08-24
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Massiceti, Daniela
  • Basu, Samyadeep
  • Stanley, Megan Jane

Abrégé

In various examples there is a computer-implemented method comprising accessing a pool of examples. The method obtains a query set comprising a plurality of held out examples in a plurality of classes. For each example in the pool, the method assigns a weight to the example and initializes the weight using a default or random value. The method accesses a constrained optimization problem. The constrained optimization is solved using a projected gradient ascent or descent, the solving resulting in optimal weights resulting in an optimal performance of a few-shot classifier on the query set, where the few-shot classifier is trained using the examples from the pool weighted by the optimal weights. The method selects, using the optimal weights, an example per class from the pool, and stores the selected examples.

Classes IPC  ?

  • G06N 3/0985 - Optimisation d’hyperparamètres; Meta-apprentissage; Apprendre à apprendre
  • G06N 20/00 - Apprentissage automatique
  • G06N 5/022 - Ingénierie de la connaissance; Acquisition de la connaissance

32.

MACHINE TEACHING WITH METHOD OF MOMENTS

      
Numéro d'application US2023030765
Numéro de publication 2024/063890
Statut Délivré - en vigueur
Date de dépôt 2023-08-22
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Maitra, Kingsuk
  • Bryant, Brendan Lee
  • Anderson, Kence

Abrégé

The techniques disclosed herein enable utilizing a full range of setpoint values to control a mechanical system. A machine learning model is trained with states collected from the mechanical system. Some of the states may have little to no variation, limiting exploration of possible setpoint values when training the model. To enable a more thorough exploration of possible setpoint values, the states are augmented with a fluctuating delta value that is derived from a fixed setpoint value. For example, a delta outside air temperature may be computed by subtracting outside air temperature, which fluctuates, from a fixed chilled water setpoint. A method of moments computation converts delta values inferred by the model back into absolute values. The absolute values are used to compute a regression equation that is usable by the mechanical system to compute a setpoint action for a given set of input states.

Classes IPC  ?

  • G05B 13/04 - Systèmes de commande adaptatifs, c. à d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques impliquant l'usage de modèles ou de simulateurs
  • G05B 13/02 - Systèmes de commande adaptatifs, c. à d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques
  • G05B 15/02 - Systèmes commandés par un calculateur électriques

33.

REDUCED USER AVAILABILITY

      
Numéro d'application US2023030774
Numéro de publication 2024/063891
Statut Délivré - en vigueur
Date de dépôt 2023-08-22
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Netes, Nir
  • Ryager, Knut Harald
  • Bonyadi, Mohammdreza
  • Brugård, Håkon Bergland
  • Sommerfelt, Espen
  • Flagstad, Tinus Sola
  • Paruch, Malgorzata
  • Mwangi, Violet Wangui
  • Fiskerud, Erlend

Abrégé

Systems and methods for inferring and notifying an end user about reduced availability of a target user or group of target users in a time range of interest. For instance, the reduced availability service includes components for collecting calendar event information and calendar settings information corresponding to a calendar of a target user, generating an interval graph data structure based on the collected calendar information, determining working hours for the target user, identifying periods of time where reduced availability is determined in the target user's calendar, and generating a notification of the target user's reduced availability for alerting the end user.

Classes IPC  ?

  • G06Q 10/0631 - Planification, affectation, distribution ou ordonnancement de ressources d’entreprises ou d’organisations
  • G06Q 10/1093 - Ordonnancement basé sur un agenda pour des personnes ou des groupes
  • G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p.ex. des menus

34.

REDUCED DENSITY MATRIX ESTIMATION FOR PARTICLE-NUMBER-CONSERVING FERMION SYSTEMS USING CLASSICAL SHADOWS

      
Numéro d'application US2023023806
Numéro de publication 2024/063813
Statut Délivré - en vigueur
Date de dépôt 2023-05-30
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s) Low, Guang Hao

Abrégé

kkkkk-RDM element.

35.

MODELLING CAUSATION IN MACHINE LEARNING

      
Numéro d'application US2023031000
Numéro de publication 2024/063907
Statut Délivré - en vigueur
Date de dépôt 2023-08-24
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Gong, Wenbo
  • Zhang, Cheng
  • Pawlowski, Nick
  • Jennings, Joel
  • Fassio, Karen
  • Defante, Marife
  • Thomas, Steve
  • Horan, Alice
  • Ma, Chao
  • Ashman, Matthew
  • Hilmkil, Agrin

Abrégé

A method comprising: sampling a temporal causal graph from a temporal graph distribution specifying probabilities of directed causal edges between different variables of a feature vector at a present time step, and from one variable at a preceding time step to another variables at the present time step. Based on this there are identified: a present parent which is a cause of the selected variable in the present time step, and a preceding parent which is a cause of the selected variable from the preceding time step. The method then comprises: inputting a value of each identified present and preceding parent into a respective encoder, resulting in a respective embedding of each of the present and preceding parents; combining the embeddings of the present and preceding parents, resulting in a combined embedding; inputting the combined embedding into a decoder, resulting in a reconstructed value of the selected variable.

Classes IPC  ?

  • G06N 3/0455 - Réseaux auto-encodeurs; Réseaux encodeurs-décodeurs
  • G06N 5/025 - Extraction de règles à partir de données
  • G06N 7/01 - Modèles graphiques probabilistes, p.ex. réseaux probabilistes
  • G06N 3/084 - Rétropropagation, p.ex. suivant l’algorithme du gradient
  • G06N 5/01 - Techniques de recherche dynamique; Heuristiques; Arbres dynamiques; Séparation et évaluation
  • G06N 20/20 - Techniques d’ensemble en apprentissage automatique

36.

SYSTEMS AND METHODS FOR PRESENTING VISUAL CONTENT

      
Numéro d'application 17953141
Statut En instance
Date de dépôt 2022-09-26
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Reyes, Karlo Alexis
  • Medlin, Ryan Ashley
  • Richman, Efus
  • Marshall, Ross Anthony
  • Dean, Raymond Charles
  • Covington, Kayla Louise
  • Zahand, Brannon James

Abrégé

A method of navigating visual content includes establishing an interface template including a viewport; obtaining visual content data; identifying at least one focusable element in the visual content data; presenting a first portion of visual content in the viewport on a display device, wherein the visual content is based at least partially on the visual content data; indicating a first focusable element in the viewport with a visual indicator; and responsive to a user input, scrolling the visual content in the viewport when a second focusable element of the visual content is not present in the viewport in a navigation direction of the user input.

Classes IPC  ?

  • A63F 13/53 - Commande des signaux de sortie en fonction de la progression du jeu incluant des informations visuelles supplémentaires fournies à la scène de jeu, p.ex. en surimpression pour simuler un affichage tête haute [HUD] ou pour afficher une visée laser dans un jeu de tir
  • G06F 3/04842 - Sélection des objets affichés ou des éléments de texte affichés
  • G06F 3/0485 - Défilement ou défilement panoramique

37.

DIRECT ASSIGNMENT OF PHYSICAL DEVICES TO CONFIDENTIAL VIRTUAL MACHINES

      
Numéro d'application 17953169
Statut En instance
Date de dépôt 2022-09-26
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Lin, Jin
  • Wohlgemuth, Jason Stewart
  • Ebersol, Michael Bishop
  • Bhandari, Aditya
  • West, Steven Adrian
  • Clemens, Emily Cara
  • Kelley, Michael Halstead
  • Cui, Dexuan
  • Mainetti, Attilio
  • Stephenson, Sarah Elizabeth
  • Perez-Vargas, Carolina Cecilia
  • Delignat-Lavaud, Antoine Jean Denis
  • Vaswani, Kapil
  • Grest, Alexander Daniel
  • Pronovost, Steve Michel
  • Hepkin, David Alan

Abrégé

Methods, systems, and computer program products for direct assignment of physical devices to confidential virtual machines (VMs). At a first guest privilege context of a guest partition, a direct assignment of a physical device associated with a host computer system to the guest partition is identified. The guest partition includes the first guest privilege context and a second guest privilege context, which is restricted from accessing memory associated with the first guest privilege context. The guest partition corresponds to a confidential VM, such that a memory region associated with the guest partition is inaccessible to a host operating system. It is determined, based on a policy, that the physical device is allowed to be directly assigned to the guest partition. Communication between the physical device and the second guest privilege context is permitted, such as by exposing the physical device on a virtual bus and/or forwarding an interrupt.

Classes IPC  ?

  • G06F 21/53 - Contrôle des usagers, programmes ou dispositifs de préservation de l’intégrité des plates-formes, p.ex. des processeurs, des micrologiciels ou des systèmes d’exploitation au stade de l’exécution du programme, p.ex. intégrité de la pile, débordement de tampon ou prévention d'effacement involontaire de données par exécution dans un environnement restreint, p.ex. "boîte à sable" ou machine virtuelle sécurisée
  • G06F 21/60 - Protection de données
  • G06F 21/79 - Protection de composants spécifiques internes ou périphériques, où la protection d'un composant mène à la protection de tout le calculateur pour assurer la sécurité du stockage de données dans les supports de stockage à semi-conducteurs, p.ex. les mémoires adressables directement

38.

PRIVACY TRANSFORMATIONS IN DATA ANALYTICS

      
Numéro d'application 18374316
Statut En instance
Date de dépôt 2023-09-28
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Ananthanarayanan, Ganesh
  • Cox, Landon Prentice
  • Bahl, Paramvir

Abrégé

Systems and methods are provided for performing privacy transformation of data to protect privacy in data analytics under the multi-access edge computing environment. In particular, a policy receiver in an edge server receives privacy instructions. Inference determiner in the edge server in a data analytics pipeline receives data from an IoT device and evaluates the data to recognize data associated with personally identifiable information. Privacy data transformer transforms the received data with inference for protecting data privacy by preventing exposure of private information from the edge server. In particular, the privacy data transformer dynamically selects a technique among techniques for removing information that is subject to privacy protection and transforms the received data using the technique. The techniques includes reducing resolution of image data such that inference enables object recognition without sufficient details to prevent other servers in the data analytics pipeline to determine identifies of the object deeper inferences.

Classes IPC  ?

  • G06F 21/62 - Protection de l’accès à des données via une plate-forme, p.ex. par clés ou règles de contrôle de l’accès
  • G16Y 40/50 - Sûreté; Sécurité des objets, des utilisateurs, des données ou des systèmes

39.

REDUCED USER AVAILABILITY

      
Numéro d'application 17934689
Statut En instance
Date de dépôt 2022-09-23
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Netes, Nir
  • Ryager, Knut Harald
  • Bonyadi, Mohammdreza
  • Brugård, Håkon Bergland
  • Sommerfelt, Espen
  • Flagstad, Tinus Sola
  • Paruch, Malgorzata
  • Mwangi, Violet Wangui
  • Fiskerud, Erlend

Abrégé

Systems and methods for inferring and notifying an end user about reduced availability of a target user or group of target users in a time range of interest. For instance, the reduced availability service includes components for collecting calendar event information and calendar settings information corresponding to a calendar of a target user, generating an interval graph data structure based on the collected calendar information, determining working hours for the target user, identifying periods of time where reduced availability is determined in the target user's calendar, and generating a notification of the target user's reduced availability for alerting the end user.

Classes IPC  ?

40.

SYSTEM AND METHOD FOR ML-AIDED ANOMALY DETECTION AND END-TO-END COMPARATIVE ANALYSIS OF THE EXECUTION OF SPARK JOBS WITHIN A CLUSTER

      
Numéro d'application 17954094
Statut En instance
Date de dépôt 2022-09-27
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Manohar, Nelson Roberto
  • Acharya, Vidip S
  • Wahba, Fady H

Abrégé

Example aspects include techniques for ML-aided anomaly detection and comparative analysis of execution of spark jobs within a cluster. These techniques may include collecting, by a cluster-based analytics platform, log entries generated during execution of a DDPE job using one or more services associated with the cluster-based analytics platform and generating signal information based on the log entries. In addition, the techniques may include determining anomaly information based on the signal information and historic signal information and generating a feature vector based on task information, stage information, and/or input-output information of the distributed data processing engine job. Further, the techniques may include determining similarity information based on the feature vector and the historic signal information, the similarity information identifying previously-executed DDPE jobs having a similarity value with the DDPE job above a predefined threshold and determining inference information based on the anomaly information and the similarity information.

Classes IPC  ?

  • G06F 11/07 - Réaction à l'apparition d'un défaut, p.ex. tolérance de certains défauts

41.

DEBUGGING TOOL FOR CODE GENERATION NEURAL LANGUAGE MODELS

      
Numéro d'application 18082366
Statut En instance
Date de dépôt 2022-12-15
Date de la première publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC. (USA)
Inventeur(s)
  • Clement, Colin Bruce
  • Nader Palacio, David Alberto
  • Sundaresan, Neelakantan
  • Svyatkovskiy, Alexey
  • Tufano, Michele

Abrégé

A debugging tool identifies the smallest subset of an input sequence or rationales that influenced a neural language model to generate an output sequence. The debugging tool uses the rationales to understand why the model made its predictions and in particular, the particular input tokens that had the most impact on the output sequence. In the case of erroneous output, the rationales are used to alter the input sequence to avoid the error or to tailor a new training dataset to retrain the model to improve its performance.

Classes IPC  ?

  • G06F 11/36 - Prévention d'erreurs en effectuant des tests ou par débogage de logiciel

42.

LOAD ADJUSTED POPULATIONS OF INTEGRATED CIRCUIT DECOUPLING CAPACITORS

      
Numéro d'application 18529178
Statut En instance
Date de dépôt 2023-12-05
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Calugaru, Vlad Radu
  • Hovis, William Paul

Abrégé

Techniques and systems for enhanced adjustment of quantities and placement of decoupling capacitance on circuit boards for integrated circuits is provided herein. An example method includes iterating application of a load profile across different populations of decoupling capacitors on a circuit board for supply voltage domains of an integrated circuit device until a target transient performance is reached for the supply voltage domains. The load profile is applied onto electrical connections corresponding to the supply voltage domains for the integrated circuit device. The method also includes generating a capacitor population configuration for the circuit board based on a population of the decoupling capacitors that achieves the target transient performance.

Classes IPC  ?

  • G06F 1/3296 - Gestion de l’alimentation, c. à d. passage en mode d’économie d’énergie amorcé par événements Économie d’énergie caractérisée par l'action entreprise par diminution de la tension d’alimentation ou de la tension de fonctionnement
  • G05F 1/46 - Régulation de la tension ou de l'intensité là où la variable effectivement régulée par le dispositif de réglage final est du type continu
  • G06F 30/337 - Optimisation de la conception

43.

DATABASE SIMULATION MODELING FRAMEWORK

      
Numéro d'application 18530914
Statut En instance
Date de dépôt 2023-12-06
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Ye, Zi
  • Moeller, Justin Grant
  • Lin, Ya
  • Lang, Willis

Abrégé

Methods, systems, and computer program products are provided for creating a resource management testing environment. An initial population of databases is established in a database ring, having an in initial count of databases and different types of databases that are determined based on an initial database population model. The initial population model receives ring classification information for the database ring from a ring grouping model. A sequence of database population-change events is generated based on a model, to change the population of the databases over time in the ring. An orchestration framework performs testing of resource manager operations based on the model-defined initial population of databases and the model-defined populations of databases changed over time. Model-defined resource usage metrics for each database are utilized to test the resource manager operations. Resource usage metrics and database add/drop events of a production system are used to train the models.

Classes IPC  ?

  • G06F 11/34 - Enregistrement ou évaluation statistique de l'activité du calculateur, p.ex. des interruptions ou des opérations d'entrée–sortie
  • G06F 11/30 - Surveillance du fonctionnement
  • G06F 16/21 - Conception, administration ou maintenance des bases de données
  • G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuées; Architectures de systèmes de bases de données distribuées à cet effet

44.

ADAPTIVE BATTERY MANAGEMENT

      
Numéro d'application 17955255
Statut En instance
Date de dépôt 2022-09-28
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Harrigan, Jason
  • Patana, Tero J.

Abrégé

This document generally relates to techniques for adaptively triggering charging notifications for a battery-powered user device. One example includes a method or technique that can be performed on a computing device. The method or technique can include obtaining a battery charge level of a battery of a battery-powered user device and accessing user data for a user of the battery-powered user device. The user data can reflect previous usage sessions of the user with the battery-powered user device. The method or technique can also include predicting a future usage session of the user with the battery-powered user device based on the user data. The method or technique can also include estimating confidence that the battery will last through the future usage session based on the battery charge level and the predicted future usage session. The method or technique can also include triggering a charging notification prior to the future usage session based on the estimated confidence.

Classes IPC  ?

  • H02J 7/00 - Circuits pour la charge ou la dépolarisation des batteries ou pour alimenter des charges par des batteries
  • A63F 13/235 - Dispositions d'entrée pour les dispositifs de jeu vidéo pour l'interfaçage avec le dispositif de jeu, p.ex. des interfaces spécifiques entre la manette et la console de jeu utilisant une connexion sans fil, p.ex. infrarouge ou piconet
  • A63F 13/285 - Génération de signaux de retour tactiles via le dispositif d’entrée du jeu, p.ex. retour de force

45.

Eye Contact Optimization

      
Numéro d'application 17953066
Statut En instance
Date de dépôt 2022-09-26
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Thomasian, Eric Edmond
  • Dunning, Shaun Paul
  • Hassan, Amer Aref

Abrégé

Systems and methods for conducting a videoconference including receiving multimedia streams of a plurality of participants in a multimedia conference, the multimedia streams including audio components and video components and displaying video tiles of the participants on a display screen. The audio components and/or the video components of the multimedia streams are analyzed to detect characteristics indicative of a first participant and a second participant having a first conversation with each other. Camera positions on the computing devices of the participants are identified. In response to identifying that the first participant and the second participant are having the first conversation with each other, a video tile for the first participant and a video tile for the second participant are moved to edges of the respective display screens toward the camera positions.

Classes IPC  ?

  • H04N 5/262 - Circuits de studio, p.ex. pour mélanger, commuter, changer le caractère de l'image, pour d'autres effets spéciaux
  • G06T 7/73 - Détermination de la position ou de l'orientation des objets ou des caméras utilisant des procédés basés sur les caractéristiques
  • G06V 20/40 - RECONNAISSANCE OU COMPRÉHENSION D’IMAGES OU DE VIDÉOS Éléments spécifiques à la scène dans le contenu vidéo
  • G10L 17/00 - Identification ou vérification du locuteur

46.

DETERMINING DIGITAL CONTENT SERVICE QUALITY LEVELS BASED ON CUSTOMIZED USER METRICS

      
Numéro d'application 17954177
Statut En instance
Date de dépôt 2022-09-27
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Almeida Dos Santos, José Carlos
  • Batt, Naseer Ud Din Ahmed
  • Tiwari, Prateek

Abrégé

The present disclosure relates to utilizing a content service system to improve selecting data sources that are used to retrieve digital content items in response to content requests. For example, in response to receiving a content request, the content service system determines to retrieve content items by either calling a lower-quality data source with lower computing costs based on the request having lower service quality metrics or by calling a higher-quality data source with higher computing-costs based on the request having superior service quality metrics. In many instances, the service quality metric is based on the user characteristics of a user identifier associated with the requesting device. By dynamically determining to utilize different data sources having different computing costs based on service quality metrics, the content service system significantly reduces the total amount of computing costs for retrieving and providing digital content, without hurting the user experience.

Classes IPC  ?

  • H04L 67/61 - Ordonnancement ou organisation du service des demandes d'application, p.ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises en tenant compte de la qualité de service [QoS] ou des exigences de priorité

47.

MODELLING CAUSATION IN MACHINE LEARNING

      
Numéro d'application 17936347
Statut En instance
Date de dépôt 2022-09-28
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Gong, Wenbo
  • Zhang, Cheng
  • Pawlowski, Nick
  • Jennings, Joel
  • Fassio, Karen
  • Defante, Marife
  • Thomas, Steve
  • Horan, Alice
  • Ma, Chao
  • Ashman, Matthew
  • Hilmkil, Agrin

Abrégé

A method comprising: sampling a temporal causal graph from a temporal graph distribution specifying probabilities of directed causal edges between different variables of a feature vector at a present time step, and from one variable at a preceding time step to another variables at the present time step. Based on this there are identified: a present parent which is a cause of the selected variable in the present time step, and a preceding parent which is a cause of the selected variable from the preceding time step. The method then comprises: inputting a value of each identified present and preceding parent into a respective encoder, resulting in a respective embedding of each of the present and preceding parents; combining the embeddings of the present and preceding parents, resulting in a combined embedding; inputting the combined embedding into a decoder, resulting in a reconstructed value of the selected variable.

Classes IPC  ?

  • G06N 3/04 - Architecture, p.ex. topologie d'interconnexion

48.

SYSTEMS AND METHODS FOR THERMAL SYSTEM MANAGEMENT

      
Numéro d'application 18529563
Statut En instance
Date de dépôt 2023-12-05
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Rintamaeki, Mika Juhani
  • Nielsen, Gregory Allen
  • Venkatachalam, Rajagopal K.
  • Justin, Ajit
  • Cantu De La Garza, Francisco

Abrégé

A method of thermal and power control in a computing device includes, at the computing device, initializing a thermal module of the computing device, receiving data at the thermal module from a first component assigned to an interface of the thermal module, and sending an output to a second component from the thermal module based on the data. Initializing the thermal module includes detecting a presence of a plurality of potential components of the computing device; querying each of the plurality of potential components to determine capabilities of each component; in response to the querying, for each of at least a subset of the plurality of potential components receiving identification information for the component and, based on the received identification information, configuring one or more interfaces of the plurality of predefined interfaces of the thermal module to establish communication with the sub set of components.

Classes IPC  ?

  • G06F 1/3234 - Gestion de l’alimentation, c. à d. passage en mode d’économie d’énergie amorcé par événements Économie d’énergie caractérisée par l'action entreprise
  • G05B 17/02 - Systèmes impliquant l'usage de modèles ou de simulateurs desdits systèmes électriques
  • G06F 1/20 - Moyens de refroidissement
  • G06F 1/3212 - Surveillance du niveau de charge de la batterie, p.ex. un mode d’économie d’énergie étant activé lorsque la tension de la batterie descend sous un certain niveau

49.

AUTOMATIC APPLICATION SCALING BETWEEN PRIVATE AND PUBLIC CLOUD PLATFORMS

      
Numéro d'application 18532872
Statut En instance
Date de dépôt 2023-12-07
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Ajodha, Anjay Vijendra
  • Lawson, Heath
  • Armour, David James
  • Napolitan, Scott Michael
  • Mcglynn, Matthew Joel
  • Natarajan, Shriram
  • Mendes, Ricardo Luiz Fagundes

Abrégé

Methods, systems, and computer program products are provided that automatically scale an application between private and public cloud computing platforms, while simultaneous enforcing policies ensuring private data is persistently stored on the private cloud computing platform, but not the public cloud computing platform. A traffic manager on the public platform routes traffic to instances of a web app executing on a private platform. A traffic monitor on the private platform monitors performance criteria of the private platform, and reports traffic telemetry to the traffic manager. Based on the traffic telemetry, the traffic manager may instantiate one or more instances of the web app on the public platform to handle traffic. Private data gathered by such instantiated instance(s) is persisted to storage in the private platform, but not in the public platform.

Classes IPC  ?

  • H04L 67/1001 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau pour accéder à un serveur parmi une pluralité de serveurs répliqués
  • H04L 67/1097 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau pour le stockage distribué de données dans des réseaux, p.ex. dispositions de transport pour le système de fichiers réseau [NFS], réseaux de stockage [SAN] ou stockage en réseau [NAS]
  • H04L 67/60 - Ordonnancement ou organisation du service des demandes d'application, p.ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises

50.

UNIVERSAL HIGHLIGHTER FOR CONTEXTUAL NOTETAKING

      
Numéro d'application 17950488
Statut En instance
Date de dépôt 2022-09-22
Date de la première publication 2024-03-28
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Primadona, Fnu
  • Mopati, Sivaramakrishna
  • Silvis, Jason Glenn

Abrégé

Systems and methods are provided for interactively highlighting a region as pixel data on a screen and automatically retrieving context data associated with content of the highlighted region for contextual notetaking. The highlighted region includes at least a part of one or more windows and one or more applications associated with the one or more windows. The disclosed technology determines a context associated with content of the highlighted region and automatically retrieves context data that are contextually relevant to the content. Notes data are generated based on an aggregate of the highlighted content, window-specific context data, application-specific context data, and user-specific context data. A notetaking application retrieves stored the notes data from a notes database and displays the notes data for recall and for use. The contextual notetaking enables the user reducing a burden of performing manual operations for notetaking and utilizing notes that are enriched relevant data by context.

Classes IPC  ?

  • G06F 3/0354 - Dispositifs de pointage déplacés ou positionnés par l'utilisateur; Leurs accessoires avec détection des mouvements relatifs en deux dimensions [2D] entre le dispositif de pointage ou une partie agissante dudit dispositif, et un plan ou une surface, p.ex. souris 2D, boules traçantes, crayons ou palets
  • G06F 3/038 - Dispositions de commande et d'interface à cet effet, p.ex. circuits d'attaque ou circuits de contrôle incorporés dans le dispositif
  • G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p.ex. des menus
  • G06V 30/14 - Acquisition d’images
  • G06V 30/413 - Classification de contenu, p.ex. de textes, de photographies ou de tableaux

51.

LOCALLY GENERATING PRELIMINARY INKING IMAGERY

      
Numéro d'application US2023027860
Numéro de publication 2024/063838
Statut Délivré - en vigueur
Date de dépôt 2023-07-17
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s) Patnaik, Sandeep

Abrégé

A method for rendering digital inking is presented. The method comprises receiving inking input at a local application window, and locally processing the received inking input to generate preliminary inking imagery for presentation in the local application window. Parameters of the received inking input are uploaded to a remote client for remote processing to generate finalized inking imagery. The preliminary inking imagery is updated based on the finalized inking imagery.

Classes IPC  ?

  • G06F 3/0354 - Dispositifs de pointage déplacés ou positionnés par l'utilisateur; Leurs accessoires avec détection des mouvements relatifs en deux dimensions [2D] entre le dispositif de pointage ou une partie agissante dudit dispositif, et un plan ou une surface, p.ex. souris 2D, boules traçantes, crayons ou palets
  • G06F 3/041 - Numériseurs, p.ex. pour des écrans ou des pavés tactiles, caractérisés par les moyens de transduction
  • G06F 3/04883 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] utilisant des caractéristiques spécifiques fournies par le périphérique d’entrée, p.ex. des fonctions commandées par la rotation d’une souris à deux capteurs, ou par la nature du périphérique d’entrée, p.ex. des gestes en fonction de la pression exer utilisant un écran tactile ou une tablette numérique, p.ex. entrée de commandes par des tracés gestuels pour l’entrée de données par calligraphie, p.ex. sous forme de gestes ou de texte

52.

ROUND ROBIN ARBITRATION USING RANDOM ACCESS MEMORY

      
Numéro d'application US2023030881
Numéro de publication 2024/063896
Statut Délivré - en vigueur
Date de dépôt 2023-08-23
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s) Gal, Tama

Abrégé

A circuit performs a method of arbitrating requests between multiple requestors. The method includes accessing, via an arbitration processor, a requestor random access memory (RRAM) having multiple entries. Each entry corresponds to a requestor and includes a valid field indicating whether or not the requestor is requesting. One of the multiple entries is selected in a round robin manner as a function of a value in the valid field indicative of the corresponding requestor requesting. The corresponding requestor requesting arbitration is notified.

Classes IPC  ?

  • G06F 13/16 - Gestion de demandes d'interconnexion ou de transfert pour l'accès au bus de mémoire
  • G06F 13/366 - Gestion de demandes d'interconnexion ou de transfert pour l'accès au bus ou au système à bus communs avec commande d'accès centralisée utilisant un arbitre d'interrogation centralisé

53.

NEURAL GRAPHICAL MODELS FOR GENERIC DATA TYPES

      
Numéro d'application US2023031106
Numéro de publication 2024/063914
Statut Délivré - en vigueur
Date de dépôt 2023-08-25
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Shrivastava, Harsh
  • Chajewska, Urszula Stefania

Abrégé

The present disclosure relates to methods and systems for providing a neural graphical model. The methods and systems generate a neural view of the neural graphical model for a domain. The input data is generated from the domain and includes generic input data. The input data also includes a combination of different data types of input data. The neural view of the neural graphical model represents the functions of the different features of the domain using a neural network. The functions are learned for the features of the domain using a dependency structure of an input graph for the input data and the neural network. The methods and systems use the neural graphical model to perform inference tasks. The methods and systems also use the neural graphical model to perform sampling tasks.

Classes IPC  ?

  • G06N 3/0455 - Réseaux auto-encodeurs; Réseaux encodeurs-décodeurs
  • G06N 3/047 - Réseaux probabilistes ou stochastiques
  • G06N 3/084 - Rétropropagation, p.ex. suivant l’algorithme du gradient
  • G06N 3/09 - Apprentissage supervisé

54.

NEURAL GRAPHICAL MODELS

      
Numéro d'application US2023031105
Numéro de publication 2024/063913
Statut Délivré - en vigueur
Date de dépôt 2023-08-25
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Shrivastava, Harsh
  • Chajewska, Urszula Stefania

Abrégé

The present disclosure relates to methods and systems for providing a neural graphical model. The methods and systems generate a neural view of the neural graphical model for input data. The neural view of the neural graphical model represents the functions of the different features of the domain using a neural network. The functions are learned for the features of the domain using a dependency structure of an input graph for the input data using neural network training for the neural view. The methods and systems use the neural graphical model to perform inference tasks. The methods and systems also use the neural graphical model to perform sampling tasks.

Classes IPC  ?

  • G06N 7/01 - Modèles graphiques probabilistes, p.ex. réseaux probabilistes

55.

GENERATING A GALLERY VIEW FROM AN AREA VIEW

      
Numéro d'application US2023031108
Numéro de publication 2024/063916
Statut Délivré - en vigueur
Date de dépôt 2023-08-25
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Master Ben-Dor, Karen
  • Zychlinski, Eshchar
  • Yagev, Stav
  • Smolin, Yoni
  • Halaly, Raz
  • Diamant, Adi
  • Leichter, Ido
  • Shlomi, Tamir

Abrégé

Techniques for generating a gallery view of tiles for in-area participants who are participating in an online meeting are disclosed. A video stream is accessed, where this stream includes an area view of an area in which an in-area participant is located. This area view comprises pixels representative of the area and pixels representative of the in-area participant. The pixels representative of the in-area participant are identified. A field of view of the in-area participant is generated. A tile of the in-area participant is generated based on the field of view. This tile is then displayed while the area view is not displayed.

Classes IPC  ?

56.

UNIVERSAL HIGHLIGHTER FOR CONTEXTUAL NOTETAKING

      
Numéro d'application US2023031107
Numéro de publication 2024/063915
Statut Délivré - en vigueur
Date de dépôt 2023-08-25
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Primadona, Fnu
  • Mopati, Sivaramakrishna
  • Silvis, Jason, Glenn

Abrégé

Systems and methods are provided for interactively highlighting a region as pixel data on a screen and automatically retrieving context data associated with content of the highlighted region for contextual notetaking. The highlighted region includes at least a part of one or more windows and one or more applications associated with the one or more windows. The disclosed technology determines a context associated with content of the highlighted region and automatically retrieves context data that are contextually relevant to the content. Notes data are generated based on an aggregate of the highlighted content, window-specific context data, application-specific context data, and user-specific context data. A notetaking application retrieves stored the notes data from a notes database and displays the notes data for recall and for use. The contextual notetaking enables the user reducing a burden of performing manual operations for notetaking and utilizing notes that are enriched relevant data by context.

Classes IPC  ?

  • G06F 40/166 - Traitement de texte Édition, p.ex. insertion ou suppression
  • G06F 3/04842 - Sélection des objets affichés ou des éléments de texte affichés
  • G06V 30/14 - Acquisition d’images

57.

DETECTING UPLOADS OF MALICIOUS FILES TO CLOUD STORAGE

      
Numéro d'application US2023031102
Numéro de publication 2024/063911
Statut Délivré - en vigueur
Date de dépôt 2023-08-25
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Salman, Tamer
  • Karpovsky, Andrey

Abrégé

Files uploaded to a cloud storage medium are considered. The files may include a mixture of files known to be malicious and known to be benign. The files are clustered using similarity of file features, e.g., based on distance in a feature space. File clusters may then be used to determine a threat status of an unknown file (a file whose threat status is unknown initially). A feature of the unknown file in the feature space is determined, and a distance in the feature space between the file and a file cluster is calculated. The distance between the unknown file and the file cluster is used to determine whether or not to perform a deep scan on the unknown file. If such a need is identified, and the deep scan indicates the unknown file is malicious, a cybersecurity action is triggered.

Classes IPC  ?

  • G06F 21/55 - Détection d’intrusion locale ou mise en œuvre de contre-mesures
  • H04L 9/40 - Protocoles réseaux de sécurité
  • G06F 21/53 - Contrôle des usagers, programmes ou dispositifs de préservation de l’intégrité des plates-formes, p.ex. des processeurs, des micrologiciels ou des systèmes d’exploitation au stade de l’exécution du programme, p.ex. intégrité de la pile, débordement de tampon ou prévention d'effacement involontaire de données par exécution dans un environnement restreint, p.ex. "boîte à sable" ou machine virtuelle sécurisée
  • G06F 21/56 - Détection ou gestion de programmes malveillants, p.ex. dispositions anti-virus

58.

MODELLING CAUSATION IN MACHINE LEARNING

      
Numéro d'application US2023031103
Numéro de publication 2024/063912
Statut Délivré - en vigueur
Date de dépôt 2023-08-25
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Ma, Chao
  • Zhang, Cheng
  • Ashman, Matthew
  • Defante, Marife
  • Fassio, Karen
  • Jennings, Joel
  • Hilmkil, Agrin

Abrégé

A method comprising: sampling a first causal graph from a first graph distribution modelling causation between variables in a feature vector, and sampling a second causal graph from a second graph distribution modelling presence of possible confounders, a confounder being an unobserved cause of both of two variables. The method further comprises: identifying a parent variable which is a cause of a selected variable according to the first causal graph, and which together with the selected variable forms a confounded pair having a respective confounder being a cause of both according to the second causal graph. A machine learning model encodes the parent to give a first embedding, and encodes information on the confounded pair give a second embedding. The embeddings are combined and then decoded to give a reconstructed value. This mechanism may be used in training the model or in treatment effect estimation.

Classes IPC  ?

  • G06N 3/0455 - Réseaux auto-encodeurs; Réseaux encodeurs-décodeurs
  • G06N 5/025 - Extraction de règles à partir de données
  • G06N 7/01 - Modèles graphiques probabilistes, p.ex. réseaux probabilistes
  • G06N 3/084 - Rétropropagation, p.ex. suivant l’algorithme du gradient
  • G06N 5/01 - Techniques de recherche dynamique; Heuristiques; Arbres dynamiques; Séparation et évaluation
  • G16H 20/00 - TIC spécialement adaptées aux thérapies ou aux plans d’amélioration de la santé, p.ex. pour manier les prescriptions, orienter la thérapie ou surveiller l’observance par les patients
  • G16H 50/30 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicales; TIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour l’évaluation des risques pour la santé d’une personne

59.

SENDER BASED ADAPTIVE BIT RATE CONTROL

      
Numéro d'application US2023026894
Numéro de publication 2024/063831
Statut Délivré - en vigueur
Date de dépôt 2023-07-05
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Gunnalan, Rajesh
  • Tsahhirov, Ilja
  • Konovalov, Mihhail
  • Qian, Tin

Abrégé

Techniques are described for streaming (e.g., low-latency streaming) of media content by performing sender-based adaptive bit rate control operations. The operations can include streaming a media stream to a streaming client. While streaming the media stream, an outgoing queue of buffered streaming content to be sent to the streaming client can be monitored. When a step down condition is satisfied, based at least in part on the monitoring, a switch can be made to a lower bit rate media stream for streaming to the streaming client. When a step up condition is satisfied, based at least in part on the monitoring, a switch can be made to a higher bit rate media stream for streaming to the streaming client. The operations are performed without receiving any quality feedback from the streaming client and without measuring bandwidth of the network channel.

Classes IPC  ?

  • H04L 65/752 - Gestion des paquets du réseau multimédia en adaptant les médias aux capacités du réseau
  • H04L 65/80 - Dispositions, protocoles ou services dans les réseaux de communication de paquets de données pour prendre en charge les applications en temps réel en répondant à la qualité des services [QoS]
  • H04N 21/234 - Traitement de flux vidéo élémentaires, p.ex. raccordement de flux vidéo ou transformation de graphes de scènes MPEG-4
  • H04N 21/238 - Interfaçage de la voie descendante du réseau de transmission, p.ex. adaptation du débit de transmission d'un flux vidéo à la bande passante du réseau; Traitement de flux multiplexés
  • H04N 21/2381 - Adaptation du flux multiplexé à un réseau spécifique, p.ex. un réseau à protocole Internet [IP]
  • H04N 21/24 - Surveillance de procédés ou de ressources, p.ex. surveillance de la charge du serveur, de la bande passante disponible ou des requêtes effectuées sur la voie montante

60.

APP USAGE MODELS WITH PRIVACY PROTECTION

      
Numéro d'application US2023030995
Numéro de publication 2024/063906
Statut Délivré - en vigueur
Date de dépôt 2023-08-24
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Joshi, Dhruv
  • Brown, David William
  • Sobhani, Dolly
  • Kihneman, Brian Eugene

Abrégé

Methods, systems, and computer programs are presented for generating a usage model for predicting user commands in an app. One method includes receiving model information from client devices. The model is obtained at each client device by training a machine-learning program with app usage data. The server generates synthetic data using the models from the client devices. A machine-learning program is trained using the synthetic data to obtain a global model, which receives as input information about recent commands entered on the app and generates an output with a prediction for the next command expected to be received by the app. The information of the global model is transmitted to a first client device, and the app provides at least one command option in the app user interface based on a prediction, generated by the global model, of the next command expected.

Classes IPC  ?

  • G06N 3/098 - Apprentissage distribué, p.ex. apprentissage fédéré
  • G06F 3/01 - Dispositions d'entrée ou dispositions d'entrée et de sortie combinées pour l'interaction entre l'utilisateur et le calculateur
  • G06F 21/62 - Protection de l’accès à des données via une plate-forme, p.ex. par clés ou règles de contrôle de l’accès
  • G06F 9/50 - Allocation de ressources, p.ex. de l'unité centrale de traitement [UCT]

61.

DEBUGGING TOOL FOR CODE GENERATION NEURAL LANGUAGE MODELS

      
Numéro d'application US2023030992
Numéro de publication 2024/063904
Statut Délivré - en vigueur
Date de dépôt 2023-08-24
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Clement, Colin Bruce
  • Nader Palacio, David Alberto
  • Sundaresan, Neelakantan
  • Svyatkovskiy, Alexey
  • Tufano, Michele

Abrégé

A debugging tool identifies the smallest subset of an input sequence or rationales that influenced a neural language model to generate an output sequence. The debugging tool uses the rationales to understand why the model made its predictions and in particular, the particular input tokens that had the most impact on the output sequence. In the case of erroneous output, the rationales are used to alter the input sequence to avoid the error or to tailor a new training dataset to retrain the model to improve its performance.

Classes IPC  ?

  • G06F 11/36 - Prévention d'erreurs en effectuant des tests ou par débogage de logiciel
  • G06N 3/0455 - Réseaux auto-encodeurs; Réseaux encodeurs-décodeurs
  • G06F 8/33 - Création ou génération de code source Éditeurs intelligents
  • G06N 3/042 - Réseaux neuronaux fondés sur la connaissance; Représentations logiques de réseaux neuronaux
  • G06N 3/044 - Réseaux récurrents, p.ex. réseaux de Hopfield
  • G06N 3/10 - Interfaces, langages de programmation ou boîtes à outils de développement logiciel, p.ex. pour la simulation de réseaux neuronaux
  • G06N 3/084 - Rétropropagation, p.ex. suivant l’algorithme du gradient
  • G06N 5/045 - Explication d’inférence; Intelligence artificielle explicable [XAI]; Intelligence artificielle interprétable

62.

TIMING RECOMMENDATION OF SERVER DECOMMISSIONING

      
Numéro d'application CN2022120710
Numéro de publication 2024/060168
Statut Délivré - en vigueur
Date de dépôt 2022-09-23
Date de publication 2024-03-28
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Yu, Chenmin
  • Ding, Shuiyuan
  • Xu, Huanghao
  • Han, Jiayin
  • Meng, Fanchen
  • Sang, Junjun
  • Sriperumbudur, Seshadri
  • Yeap, Boon Pin
  • Gargash, Scott
  • Fooks, Josh
  • Zhu, Ting

Abrégé

The present disclosure provides methods and apparatuses for providing timing recommendation of server decommissioning in a cloud service platform. Multi-modal data associated with decommissioning-decision made to a target server in the cloud service platform may be obtained. A maintenance cost curve of the target server and at least one of a server additional value curve of the target server and a replacement server cost line of a replacement server may be generated based on the multi-modal data. Decommissioning timing recommendation of the target server may be determined according to the maintenance cost curve and at least one of the server additional value curve and thereplacement server cost line.

Classes IPC  ?

  • G06F 9/50 - Allocation de ressources, p.ex. de l'unité centrale de traitement [UCT]
  • G06Q 10/20 - Administration de la réparation ou de la maintenance des produits

63.

Button for a computing input device

      
Numéro d'application 29837975
Numéro de brevet D1019666
Statut Délivré - en vigueur
Date de dépôt 2022-05-10
Date de la première publication 2024-03-26
Date d'octroi 2024-03-26
Propriétaire Microsoft Corporation (USA)
Inventeur(s)
  • Helmes, John
  • Adams, Aditha May
  • Dearsley, Simon Cameron
  • Osaki, Go
  • Sun, Hongshan

64.

Restricting message notifications and conversations based on device type, message category, and time period

      
Numéro d'application 18151099
Numéro de brevet 11943188
Statut Délivré - en vigueur
Date de dépôt 2023-01-06
Date de la première publication 2024-03-26
Date d'octroi 2024-03-26
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s) Rathi, Hitesh

Abrégé

A data processing system implements techniques for restricting which notifications and/or conversations are presented on a plurality of user devices associated with a user. Each user device is associated with a device category. The device categories are associated with time category information that associates each of a plurality of time periods with permitted device category information that indicates which categories of user devices associated with the user are permitted to present notifications that messages have been received for a particular time period and the categories of messages for which the notifications may be presented for that time period and/or which categories of conversations may be presented or hidden. The message category may be determined based on user input or by analyzing the message content with a machine learning model configured to predict the message category.

Classes IPC  ?

  • H04L 51/212 - Surveillance ou traitement des messages utilisant un filtrage ou un blocage sélectif
  • H04L 51/224 - Surveillance ou traitement des messages en fournissant une notification sur les messages entrants, p.ex. des poussées de notifications des messages reçus

65.

Joystick for a computing input device

      
Numéro d'application 29837973
Numéro de brevet D1019649
Statut Délivré - en vigueur
Date de dépôt 2022-05-10
Date de la première publication 2024-03-26
Date d'octroi 2024-03-26
Propriétaire Microsoft Corporation (USA)
Inventeur(s)
  • Helmes, John
  • Adams, Aditha May
  • Dearsley, Simon Cameron
  • Osaki, Go
  • Sun, Hongshan

66.

Zero-trust DNS and FQDN based traffic acquisition using synthetic IP

      
Numéro d'application 18099417
Numéro de brevet 11943195
Statut Délivré - en vigueur
Date de dépôt 2023-01-20
Date de la première publication 2024-03-26
Date d'octroi 2024-03-26
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Jain, Ashish
  • Gendelman, Mordhai
  • Moran, Or
  • Kattan, Omer
  • Tor, Yair
  • Goldsmith, Ronen Shmuel
  • Barak, Liraz

Abrégé

A computing system is configured to perform zero-trust domain name resolution. The computing system includes applications coupled to a zero-trust client. The zero-trust client is configured to receive requests for IP addresses corresponding to endpoint identifiers for internet connected endpoints. The zero-trust client includes a synthetic DNS service configured to identify synthetic IP addresses for the endpoint identifiers. The zero-trust client provides the synthetic IP addresses for the endpoint identifiers to the applications. The zero-trust client sends data traffic from the applications to a zero-trust service with the synthetic IP addresses and sends corresponding endpoint identifiers to the zero-trust service in a fashion that allows the synthetic IP addresses to be correlated to the endpoint identifiers at the zero-trust service.

Classes IPC  ?

  • H04L 61/2592 - Traduction d'adresses de protocole Internet [IP] en utilisant la tunnelisation ou l'encapsulation
  • H04L 61/4511 - Répertoires de réseau; Correspondance nom-adresse en utilisant des protocoles normalisés d'accès aux répertoires en utilisant le système de noms de domaine [DNS]

67.

INTERACTIVE NOTIFICATION PANELS IN A COMPUTING SYSTEM

      
Numéro d'application 18513455
Statut En instance
Date de dépôt 2023-11-17
Date de la première publication 2024-03-21
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Lewallen, Jr., James Henry
  • Mullins, Christopher Lee

Abrégé

Described herein are systems and methods for providing interactive notification panels to a user. A bot apparatus receives a notification from an application program and transforms the notification into one or more interactive notification panels configured to receive user inputs and/or to provide an output to at least one user input. Based on at least one user input, the bot apparatus transmits data to the application program, which causes the application program to perform one or more actions.

Classes IPC  ?

  • H04L 67/55 - Services réseau par poussée
  • G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p.ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comport
  • G06F 9/54 - Communication interprogramme

68.

INTEGRATING MODEL REUSE WITH MODEL RETRAINING FOR VIDEO ANALYTICS

      
Numéro d'application 18078402
Statut En instance
Date de dépôt 2022-12-09
Date de la première publication 2024-03-21
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Ananthanarayanan, Ganesh
  • Shu, Yuanchao
  • Bahl, Paramvir
  • Hsieh, Tsuwang

Abrégé

Systems and methods are provided for reusing and retraining an image recognition model for video analytics. The image recognition model is used for inferring a frame of video data that is captured at edge devices. The edge devices periodically or under predetermined conditions transmits a captured frame of video data to perform inferencing. The disclosed technology is directed to select an image recognition model from a model store for reusing or for retraining. A model selector uses a gating network model to determine ranked candidate models for validation. The validation includes iterations of retraining the image recognition model and stopping the iteration when a rate of improving accuracy by retraining becomes smaller than the previous iteration step. Retraining a model includes generating reference data using a teacher model and retraining the model using the reference data. Integrating reuse and retraining of models enables improvement in accuracy and efficiency.

Classes IPC  ?

  • G06V 10/77 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p.ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]; Séparation aveugle de source

69.

STOCHASTICITY MITIGATION IN DEPLOYED AI AGENTS

      
Numéro d'application 17933362
Statut En instance
Date de dépôt 2022-09-19
Date de la première publication 2024-03-21
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Maitra, Kingsuk
  • Bryant, Brendan Lee
  • Premoe, Chris Allen
  • Anderson, Kence

Abrégé

The techniques disclosed herein mitigate stochasticity when controlling a mechanical system with artificial intelligence (AI) agents. In some configurations, AI agents are created using data generated by a machine learning model. Stochasticity is segmented temporally into near term and long term, and different strategies are used to address stochasticity in the different timeframes. For example, long term stochasticity may be addressed with changes to the reward function used to train the model. Short term stochasticity may be addressed by applying a margin to the output of an AI agent. Example margins include window averaging, clamps, and statistical process control bounds. In one configuration, AI agents are regression brains that are generated from setpoints inferred by the model from environmental states. The limitations inherent to fitting a regression line to this data may result in some predicted setpoints being outside of an allowed range.

Classes IPC  ?

  • G05B 13/02 - Systèmes de commande adaptatifs, c. à d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé électriques
  • F24F 11/64 - Traitement électronique utilisant des données mémorisées au préalable

70.

PROXIMITY-TRIGGERED DELIVERY OF PEOPLE HIGHLIGHTS

      
Numéro d'application 17946680
Statut En instance
Date de dépôt 2022-09-16
Date de la première publication 2024-03-21
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s) Øhrn, Aleksander

Abrégé

A computer-implemented method of proximity-triggered delivery of people highlights can include receiving a plurality of highlight requests from a plurality of users; determining, from the plurality of highlight requests, that a first user of the plurality of users is physically proximate to a second user of the plurality of users; accessing information associated with the first user and accessing information associated with the second user; determining a relationship between the first user and the second user based on the information associated with the first user and the information associated with the second user; and obtaining a highlight based on the determined relationship between the first user and the second user.

Classes IPC  ?

  • H04L 67/52 - Services réseau spécialement adaptés à l'emplacement du terminal utilisateur
  • H04L 67/55 - Services réseau par poussée

71.

REAL-TIME EVENT DATA REPORTING ON EDGE COMPUTING DEVICES

      
Numéro d'application 17946484
Statut En instance
Date de dépôt 2022-09-16
Date de la première publication 2024-03-21
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Patro, Sameer Kumar
  • Basu, Aritra
  • Kumar, Arun

Abrégé

The present disclosure relates to utilizing a real-time event data reporting system that makes real-time and near-real-time monitoring and reporting possible in edge devices. For example, in various instances, the real-time event data reporting system embeds services within traditional event data collectors of edge devices to obtain, organize, and publish event data for local computing devices in real time utilizing in-memory storage. Additionally, the real-time event data reporting system further processes the published event data to generate aggregated data that is persisted to a persistence storage. In this manner, the real-time reporting system efficiently and accurately provides event data reports to client devices with processed metric data in real time, or in near-real time when utilizing additional fallback safeguards. Indeed, the real-time reporting system provides a highly available, fault-tolerant, distributed, scalable, and efficient mechanism for collecting and managing various metrics from services in edge or cloud environments.

Classes IPC  ?

  • G06F 9/54 - Communication interprogramme
  • G06F 11/34 - Enregistrement ou évaluation statistique de l'activité du calculateur, p.ex. des interruptions ou des opérations d'entrée–sortie

72.

DYNAMICALLY SWITCHING DISPLAY IN USE BASED ON TEMPERATURE

      
Numéro d'application 17754695
Statut En instance
Date de dépôt 2020-09-17
Date de la première publication 2024-03-21
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Zhao, Zenghui
  • Ho, Chau Van

Abrégé

A device comprising a display and a display controller. The display comprises a first display portion and a second display portion. The display controller is configured to assess a temperature condition of a surface of the first display portion; and responsive to the temperature condition, to initiate a switching of display content from one of the display portions to the other display portion.

Classes IPC  ?

  • G06F 1/20 - Moyens de refroidissement
  • G06F 1/16 - TRAITEMENT ÉLECTRIQUE DE DONNÉES NUMÉRIQUES - Détails non couverts par les groupes et - Détails ou dispositions de structure
  • G06F 1/3234 - Gestion de l’alimentation, c. à d. passage en mode d’économie d’énergie amorcé par événements Économie d’énergie caractérisée par l'action entreprise
  • G06F 3/14 - Sortie numérique vers un dispositif de visualisation

73.

TOUCH SCREEN DISPLAY WITH VIRTUAL TRACKPAD

      
Numéro d'application 18523603
Statut En instance
Date de dépôt 2023-11-29
Date de la première publication 2024-03-21
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Slassi, Matan
  • Birenberg, Dmitry
  • Pundak, Gilad
  • Linenberg, Nadav
  • Mittereder, Andrew Pyon

Abrégé

Examples are disclosed relating to computing devices and methods for performing touch detection within a virtual trackpad area of a touch screen display. In one example, a non-trackpad touch input signal is received from outside the virtual trackpad area and processed with at least a jitter restrictor algorithm that applies a non-trackpad distance between reported touch locations. A virtual trackpad touch input signal is received from within the virtual trackpad area. On condition of determining that the virtual trackpad touch input signal is received from within the virtual trackpad area, the virtual trackpad touch input signal is processed with the jitter restrictor algorithm that applies a virtual trackpad distance between reported touch locations that is smaller than the non-trackpad distance between reported touch locations.

Classes IPC  ?

  • G06F 3/04886 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] utilisant des caractéristiques spécifiques fournies par le périphérique d’entrée, p.ex. des fonctions commandées par la rotation d’une souris à deux capteurs, ou par la nature du périphérique d’entrée, p.ex. des gestes en fonction de la pression exer utilisant un écran tactile ou une tablette numérique, p.ex. entrée de commandes par des tracés gestuels par partition en zones à commande indépendante de la surface d’affichage de l’écran tactile ou de la tablette numérique, p.ex. claviers virtuels ou menus
  • G06F 3/041 - Numériseurs, p.ex. pour des écrans ou des pavés tactiles, caractérisés par les moyens de transduction

74.

SHARING NEIGHBORING MAP DATA ACROSS DEVICES

      
Numéro d'application 18522989
Statut En instance
Date de dépôt 2023-11-29
Date de la première publication 2024-03-21
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Eade, Ethan
  • Vanturennout, Jeroen
  • Lyons, Jonathan
  • Fields, David
  • Lazarow, Gavin Dean
  • Bhatnagar, Tushar Cyril

Abrégé

A computing device and method are provided for transmitting a relevant subset of map data, called a neighborhood, to enable mutual spatial understanding by multiple display devices around a target virtual location to display a shared hologram in the same exact location in the physical environment at the same moment in time. The computing device may comprise a processor, a memory operatively coupled to the processor, and an anchor transfer program stored in the memory and executed by the processor.

Classes IPC  ?

  • G06F 3/14 - Sortie numérique vers un dispositif de visualisation
  • B65G 1/04 - Dispositifs d'emmagasinage mécaniques
  • G02B 27/01 - Dispositifs d'affichage "tête haute"
  • G03H 1/00 - Procédés ou appareils holographiques utilisant la lumière, les infrarouges ou les ultraviolets pour obtenir des hologrammes ou pour en obtenir une image; Leurs détails spécifiques
  • G03H 1/22 - Procédés ou appareils pour obtenir une image optique à partir d'un hologramme
  • G06F 3/01 - Dispositions d'entrée ou dispositions d'entrée et de sortie combinées pour l'interaction entre l'utilisateur et le calculateur
  • G06F 3/04815 - Interaction s’effectuant dans un environnement basé sur des métaphores ou des objets avec un affichage tridimensionnel, p.ex. modification du point de vue de l’utilisateur par rapport à l’environnement ou l’objet
  • G06F 3/147 - Sortie numérique vers un dispositif de visualisation utilisant des panneaux de visualisation
  • G06T 19/00 - Transformation de modèles ou d'images tridimensionnels [3D] pour infographie
  • G09G 3/00 - Dispositions ou circuits de commande présentant un intérêt uniquement pour l'affichage utilisant des moyens de visualisation autres que les tubes à rayons cathodiques

75.

EFFICIENTLY INTERCONNECTING COMPUTING NODES TO ENABLE USE OF HIGH-RADIX NETWORK SWITCHES

      
Numéro d'application 18520339
Statut En instance
Date de dépôt 2023-11-27
Date de la première publication 2024-03-21
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Ballani, Hitesh
  • Saunders, Winston Allen
  • Belady, Christian L.
  • Hsu, Lisa Ru-Feng
  • Costa, Paolo
  • Carmean, Douglas M.

Abrégé

A system for efficiently interconnecting computing nodes can include a plurality of computing nodes and a plurality of network switches coupled in parallel to the plurality of computing nodes. The system can also include a plurality of node interfaces. Each computing node among the plurality of computing nodes can include at least one node interface for each network switch among the plurality of network switches. The plurality of node interfaces corresponding to a computing node can be configured to send data to another computing node via the plurality of network switches. The system can also include a plurality of switch interfaces. Each network switch among the plurality of network switches can include at least one switch interface for each computing node among the plurality of computing nodes. A switch interface corresponding to the computing node can be coupled to a node interface corresponding to the computing node.

Classes IPC  ?

  • H04Q 11/00 - Dispositifs de sélection pour systèmes multiplex

76.

TENANT-CONTROLLED CLOUD UPDATES

      
Numéro d'application 18521241
Statut En instance
Date de dépôt 2023-11-28
Date de la première publication 2024-03-21
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Zhang, Jiaxing
  • Moscibroda, Thomas
  • Wang, Haoran
  • Willis, Jurgen Aubrey
  • Chen, Yang
  • Yan, Ying
  • Johnson, James E.
  • Mani, Ajay

Abrégé

Systems and methods are taught for providing customers of a cloud computing service to control when updates affect the services provided to the customers. Because multiple customers share the cloud's infrastructure, each customer may have conflicting preferences for when an update and associated downtime occurs. Preventing and resolving conflicts between the preferences of multiple customers while providing them with input for scheduling a planned update may reduce the inconvenience posed by updates. Additionally, the schedule for the update may be transmitted to customers so that they can prepare for the downtime of services associated with the update.

Classes IPC  ?

  • G06F 9/455 - Dispositions pour exécuter des programmes spécifiques Émulation; Interprétation; Simulation de logiciel, p.ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
  • G06F 8/65 - Mises à jour
  • G06F 8/656 - Mises à jour pendant le fonctionnement
  • G06F 9/48 - Lancement de programmes; Commutation de programmes, p.ex. par interruption
  • G06F 9/50 - Allocation de ressources, p.ex. de l'unité centrale de traitement [UCT]

77.

OVERFLOW APPLICATION TOOL FOR COMPUTING DEVICES

      
Numéro d'application 18523451
Statut En instance
Date de dépôt 2023-11-29
Date de la première publication 2024-03-21
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Taylor, Jr., Charles Edward
  • Hammerquist, Peter E.
  • Schoepke, Benjamin J.
  • Douma, Jessica Leigh
  • Yih, Albert Peter
  • Nobrega, Emilia Marie
  • Griffin, Hadley Meryl
  • Ferguson, Ashley Nicole
  • Disano, Robert Joseph

Abrégé

Computerized systems and methods are provided for automatically generating an application overflow tool that is dynamically updated and arranged to provide improved access to popular or recently used applications. These systems and methods improve existing technologies by generating an overflow panel different from a task bar, such that the overflow panel provides access to most recently used applications that are not on the task bar. As such, ease of access to applications is improved to increase user efficiency. These systems also improve the way computers operate by leveraging existing GUI layouts to reduce computing resource consumption, such as memory, network latency, I/O, and the like, that would otherwise be required improve access to applications.

Classes IPC  ?

  • G06F 3/04845 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p.ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs pour la transformation d’images, p.ex. glissement, rotation, agrandissement ou changement de couleur
  • G06F 3/04817 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p.ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comport utilisant des icônes
  • G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p.ex. des menus
  • G06F 3/0485 - Défilement ou défilement panoramique
  • G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur

78.

MULTI-PLATFORM PROCESS SERVICE

      
Numéro d'application 18066486
Statut En instance
Date de dépôt 2022-12-15
Date de la première publication 2024-03-21
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s) Gilman, Jonathan Andrew

Abrégé

Execution of a process using a select platform-specific process application is provided, including identifying, from a set of received inputs, a collection of selection input parameter values uniquely associated in memory with a select platform-specific process application among different platform-specific process applications configured to implement a process of a process type, identifying a process population template associated in memory with the select platform-specific process application, the process population template identifying data input fields accepted as inputs to the select platform-specific process application, receiving, from a uniform user interface, a set of user inputs, and executing the process population template. The executing includes modifying the set of user inputs to generate modified inputs of a form consistent with the data input fields accepted as inputs to the select platform-specific process application and executing the select platform specific process application based on the modified inputs.

Classes IPC  ?

  • G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
  • G06F 9/46 - Dispositions pour la multiprogrammation

79.

APP USAGE MODELS WITH PRIVACY PROTECTION

      
Numéro d'application 17948942
Statut En instance
Date de dépôt 2022-09-20
Date de la première publication 2024-03-21
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Joshi, Dhruv
  • Brown, David William
  • Sobhani, Dolly
  • Kihneman, Brian Eugene

Abrégé

Methods, systems, and computer programs are presented for generating a usage model for predicting user commands in an app. One method includes receiving model information from client devices. The model is obtained at each client device by training a machine-learning program with app usage data. The server generates synthetic data using the models from the client devices. A machine-learning program is trained using the synthetic data to obtain a global model, which receives as input information about recent commands entered on the app and generates an output with a prediction for the next command expected to be received by the app. The information of the global model is transmitted to a first client device, and the app provides at least one command option in the app user interface based on a prediction, generated by the global model, of the next command expected.

Classes IPC  ?

  • G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
  • G06F 21/62 - Protection de l’accès à des données via une plate-forme, p.ex. par clés ou règles de contrôle de l’accès

80.

LOCALLY GENERATING PRELIMINARY INKING IMAGERY

      
Numéro d'application 17933233
Statut En instance
Date de dépôt 2022-09-19
Date de la première publication 2024-03-21
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s) Patnaik, Sandeep

Abrégé

A method for rendering digital inking is presented. The method comprises receiving inking input at a local application window, and locally processing the received inking input to generate preliminary inking imagery for presentation in the local application window. Parameters of the received inking input are uploaded to a remote client for remote processing to generate finalized inking imagery. The preliminary inking imagery is updated based on the finalized inking imagery.

Classes IPC  ?

  • G06F 3/04883 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] utilisant des caractéristiques spécifiques fournies par le périphérique d’entrée, p.ex. des fonctions commandées par la rotation d’une souris à deux capteurs, ou par la nature du périphérique d’entrée, p.ex. des gestes en fonction de la pression exer utilisant un écran tactile ou une tablette numérique, p.ex. entrée de commandes par des tracés gestuels pour l’entrée de données par calligraphie, p.ex. sous forme de gestes ou de texte
  • G06F 9/451 - Dispositions d’exécution pour interfaces utilisateur
  • G06T 11/20 - Traçage à partir d'éléments de base, p.ex. de lignes ou de cercles
  • H04L 67/2869 - Terminaux spécialement adaptés à la communication

81.

DETECTING UPLOADS OF MALICIOUS FILES TO CLOUD STORAGE

      
Numéro d'application 18066987
Statut En instance
Date de dépôt 2022-12-15
Date de la première publication 2024-03-21
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Salman, Tamer
  • Karpovsky, Andrey

Abrégé

Files uploaded to a cloud storage medium are considered. The files may include a mixture of files known to be malicious and known to be benign. The files are clustered using similarity of file features, e.g., based on distance in a feature space. File clusters may then be used to determine a threat status of an unknown file (a file whose threat status is unknown initially). A feature of the unknown file in the feature space is determined, and a distance in the feature space between the file and a file cluster is calculated. The distance between the unknown file and the file cluster is used to determine whether or not to perform a deep scan on the unknown file. If such a need is identified, and the deep scan indicates the unknown file is malicious, a cybersecurity action is triggered.

Classes IPC  ?

  • G06F 21/55 - Détection d’intrusion locale ou mise en œuvre de contre-mesures

82.

SOFTWARE DEVELOPMENT QUALITY ASSESSMENT

      
Numéro d'application 17946168
Statut En instance
Date de dépôt 2022-09-16
Date de la première publication 2024-03-21
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Fanning, Michael C.
  • Mukherjee, Suvam
  • Gonzalez, Danielle Nicole
  • Faucon, Christopher Michael Henry
  • Prakash, Pragya

Abrégé

Static analysis of a code base is expanded beyond finding faults to also find code instances where a particular fault could have occurred but did not. A conformance count reflects code portions that satisfy a specified coding rule per static analysis, and a nonconformance count reflects code portions that do not satisfy the coding rule. Various metrics computed from the conformance count and nonconformance count drive software development quality assessments. For example, bugs or bug categories may be prioritized for developer attention, static analysis tools are evaluated based on the metrics, to reduce noise by eliminating low-value bug alerts. Particular areas of expertise of developers and developer groups are objectively identified. Source code editors are enhanced to provide specific recommendations in context. Other quality enhancements are also provided.

Classes IPC  ?

83.

CUSTOM DATA INDICATING NOMINAL RANGE OF SAMPLES OF MEDIA CONTENT

      
Numéro d'application 18384059
Statut En instance
Date de dépôt 2023-10-26
Date de la première publication 2024-03-21
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Wu, Yongjun
  • Thumpudi, Naveen
  • Sadhwani, Shyam

Abrégé

A media processing tool adds custom data to an elementary media bitstream or media container. The custom data indicates nominal range of samples of media content, but the meaning of the custom data is not defined in the codec format or media container format. For example, the custom data indicates the nominal range is full range or limited range. For playback, a media processing tool parses the custom data and determines an indication of media content type. A rendering engine performs color conversion operations whose logic changes based at least in part on the media content type. In this way, a codec format or media container format can in effect be extended to support full nominal range media content as well as limited nominal range media content, and hence preserve full or correct color fidelity, while maintaining backward compatibility and conformance with the codec format or media container format.

Classes IPC  ?

  • H04N 21/2383 - Codage de canal d'un flux binaire numérique, p.ex. modulation
  • H04N 21/2343 - Traitement de flux vidéo élémentaires, p.ex. raccordement de flux vidéo ou transformation de graphes de scènes MPEG-4 impliquant des opérations de reformatage de signaux vidéo pour la distribution ou la mise en conformité avec les requêtes des utilisateurs finaux ou les exigences des dispositifs des utilisateurs finaux
  • H04N 21/235 - Traitement de données additionnelles, p.ex. brouillage de données additionnelles ou traitement de descripteurs de contenu
  • H04N 21/438 - Interfaçage de la voie descendante du réseau de transmission provenant d'un serveur, p.ex. récupération de paquets MPEG d'un réseau IP
  • H04N 21/84 - Génération ou traitement de données de description, p.ex. descripteurs de contenu

84.

NON-DISRUPTIVE SERVICING COMPONENTS OF A USER MODE PROCESS

      
Numéro d'application 17932872
Statut En instance
Date de dépôt 2022-09-16
Date de la première publication 2024-03-21
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Retzlaff, Robert Tyler
  • Cardona, Omar
  • Zhou, Jie
  • Malloy, Dmitry

Abrégé

Examples of the present disclosure describe systems and methods for the non-disruptive servicing of components of a user mode process. In examples, a user mode process comprises multiple components, each encapsulating a distinct piece of functionality. A replacement component is loaded and initialized. The replacement component is validated to ensure that the required dependencies of the replacement component are satisfied by the other components of the user mode process. The component to be serviced and the components having dependencies on the component to be serviced are suspended to enable a snapshot of the runtime state of the component to be serviced to be captured. The runtime state is copied to the replacement component and the components having dependencies on the component to be serviced are updated to reference the replacement component. The replacement component is executed and the suspended components are resumed. The component to be serviced is unloaded.

Classes IPC  ?

  • G06F 8/10 - Analyse des exigences; Techniques de spécification
  • G06F 8/70 - Maintenance ou gestion de logiciel

85.

AUTONOMOUS QUOTA MANAGEMENT FOR SHARED RESOURCES

      
Numéro d'application CN2022118297
Numéro de publication 2024/055139
Statut Délivré - en vigueur
Date de dépôt 2022-09-13
Date de publication 2024-03-21
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Zhang, Hui
  • Dong, Hang
  • Lin, Zinan
  • Patel, Shruti
  • Qiao, Bo
  • Qin, Si
  • Qu, Xinge
  • Yang, Tao
  • Yu, Ye

Abrégé

The present disclosure proposes a method, apparatus and computer program product for autonomous quota management for shared resources. A quota change request may be received, the quota change request indicating a requirement to increase or decrease a quota for a shared resource of a user. A scenario corresponding to the quota change request may be identified. A set of rules for the scenario may be obtained. A decision on the quota change request may be made with the set of rules. The quota for the shared resource of the user may be managed based on the decision. The present disclosure also proposes an autonomous quota management system comprising a decision module, an execution module and a data support module.

Classes IPC  ?

  • G06F 9/50 - Allocation de ressources, p.ex. de l'unité centrale de traitement [UCT]
  • G06Q 10/0631 - Planification, affectation, distribution ou ordonnancement de ressources d’entreprises ou d’organisations

86.

COMPUTING DEVICE WITH HAPTIC TRACKPAD

      
Numéro d'application US2023020098
Numéro de publication 2024/058828
Statut Délivré - en vigueur
Date de dépôt 2023-04-27
Date de publication 2024-03-21
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Dani, Adwaita Anil
  • Kim, Donghwi
  • Zannier, Federico

Abrégé

Computing devices and methods for adjusting a driving signal for a haptic trackpad are disclosed. In one example, a computing device comprises a trackpad that comprises a printed circuit board. An accelerometer is affixed to the printed circuit board and a haptic actuator is coupled to the trackpad. A memory stores instructions executable by a processor to drive the haptic actuator to cause a first trackpad acceleration. The accelerometer measures the first trackpad acceleration, and an acceleration variance is determined by comparing the first trackpad acceleration to a target acceleration. The acceleration variance is used to adjust a driving signal for the haptic actuator to an adjusted driving signal. The haptic actuator is driven with the adjusted driving signal to cause a second trackpad acceleration different from the first trackpad acceleration.

Classes IPC  ?

  • G06F 3/01 - Dispositions d'entrée ou dispositions d'entrée et de sortie combinées pour l'interaction entre l'utilisateur et le calculateur
  • G06F 3/041 - Numériseurs, p.ex. pour des écrans ou des pavés tactiles, caractérisés par les moyens de transduction
  • G06F 3/044 - Numériseurs, p.ex. pour des écrans ou des pavés tactiles, caractérisés par les moyens de transduction par des moyens capacitifs
  • G06F 3/0354 - Dispositifs de pointage déplacés ou positionnés par l'utilisateur; Leurs accessoires avec détection des mouvements relatifs en deux dimensions [2D] entre le dispositif de pointage ou une partie agissante dudit dispositif, et un plan ou une surface, p.ex. souris 2D, boules traçantes, crayons ou palets

87.

MEMORY BUFFER MANAGEMENT ON HARDWARE DEVICES UTILIZING DISTRIBUTED DECENTRALIZED MEMORY BUFFER MONITORING

      
Numéro d'application US2023030411
Numéro de publication 2024/058895
Statut Délivré - en vigueur
Date de dépôt 2023-08-17
Date de publication 2024-03-21
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Yuan, Yi
  • Ravichandran, Narayanan
  • Groza, Robert, Jr
  • Yankilevich, Yevgeny
  • Angepat, Hari Daas

Abrégé

The present disclosure relates to utilizing a buffer management system to efficiently manage and deallocate memory buffers utilized by multiple processing roles on computer hardware devices. For example, the buffer management system utilizes distributed decentralized memory buffer monitoring in connection with augmented buffer pointers to deallocate memory buffers accurately and efficiently. In this manner, the buffer management system provides an efficient approach for multiple processing roles to consume source data stored in a memory buffer and to deallocate the buffer only after all roles have finished using it.

Classes IPC  ?

  • G06F 9/48 - Lancement de programmes; Commutation de programmes, p.ex. par interruption
  • G06F 9/50 - Allocation de ressources, p.ex. de l'unité centrale de traitement [UCT]
  • G06F 12/02 - Adressage ou affectation; Réadressage

88.

DECRYPTION KEY GENERATION AND RECOVERY

      
Numéro d'application US2023030412
Numéro de publication 2024/058896
Statut Délivré - en vigueur
Date de dépôt 2023-08-17
Date de publication 2024-03-21
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Venkatesan, Ramarathnam
  • Chandran, Nishanth

Abrégé

A decryption key is recovered that is utilized to decrypt an encrypted resource. One or more location attribute policy (LAP) servers determine whether a user attempting to access a resource has the necessary attributes to access the resource and is in a valid location in which the user is required to be to access the resource. The attributes and location are defined by a policy assigned to the resource. To verify that the user has the required attributes, the LAP server(s) request a cryptographic proof from the user that proves that the user has the required attributes. Upon validating the proof, a first portion of the decryption key is released. The LAP server(s) release a second portion of the decryption key after verifying that the user is in the required location. The LAP server(s) generate the decryption key based on the released portions.

Classes IPC  ?

  • H04L 9/32 - Dispositions pour les communications secrètes ou protégées; Protocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
  • H04L 9/08 - Répartition de clés

89.

PERSONALIZED ADAPTIVE MEETING PLAYBACK

      
Numéro d'application US2023030744
Numéro de publication 2024/058909
Statut Délivré - en vigueur
Date de dépôt 2023-08-21
Date de publication 2024-03-21
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Miller, Adi L.
  • Somech, Haim
  • Nahir, Oded

Abrégé

Technology is disclosed for programmatically determining, for a segment of a meeting recording, a user-specific adaptive playback speed, and generating a time-stretched segment playable at the adaptive playback speed. The adaptive playback speed is faster or slower than a default playback speed of the meeting recording. To determine the adaptive playback speed, this disclosure provides technologies to determine a playback data feature based on user-meeting data. The adaptive playback is generated based on the playback data feature. The segment is time-stretched to the adaptive playback speed to generate an updated meeting recording including the segment that is time-stretched and playable at the adaptive playback speed. In this manner, an updated meeting recording, specific to a user, and playable at an adaptive playback speed based on user-meeting data may reduce bandwidth associated with user's manually editing videos or rewinding playback, while improving user experience.

Classes IPC  ?

  • G11B 27/00 - Montage; Indexation; Adressage; Minutage ou synchronisation; Contrôle; Mesure de l'avancement d'une bande
  • G10L 21/043 - Compression ou expansion temporelles par changement de la vitesse
  • G10L 25/78 - Détection de la présence ou de l’absence de signaux de voix
  • H04L 12/18 - Dispositions pour la fourniture de services particuliers aux abonnés pour la diffusion ou les conférences
  • H04N 7/15 - Systèmes pour conférences
  • G11B 27/28 - Indexation; Adressage; Minutage ou synchronisation; Mesure de l'avancement d'une bande en utilisant une information détectable sur le support d'enregistrement en utilisant des signaux d'information enregistrés par le même procédé que pour l'enregistrement principal
  • G11B 27/34 - Aménagements indicateurs

90.

MICROSERVICE TERMINATION WHILE MAINTAINING HIGH AVAILABILITY

      
Numéro d'application US2023030751
Numéro de publication 2024/058912
Statut Délivré - en vigueur
Date de dépôt 2023-08-22
Date de publication 2024-03-21
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Kanso, Ali
  • Subramanian, Karthik Maharajan Sankara

Abrégé

The techniques disclosed herein enable systems to reduce the time required to terminate a set of microservices for an application while ensuring high availability and preventing request failures. This is accomplished through a termination manager which retrieves request queues for the microservices to analyze outstanding requests that require processing prior to termination. Based on the outstanding requests, the termination manager constructs call graphs for each request. The call graphs capture the operational flow of the associated request by defining a sequence of microservices whose functionality is invoked by the request. From an initial analysis, the termination manager can determine that some of the microservices do not appear in the call graphs, indicating that the microservices are not needed to process the outstanding requests. Accordingly, the unneeded microservices are terminated. As requests are processed by the remaining microservices, the termination manager gradually terminates the remaining microservices based on the call graphs.

Classes IPC  ?

  • G06F 9/48 - Lancement de programmes; Commutation de programmes, p.ex. par interruption
  • G06F 9/50 - Allocation de ressources, p.ex. de l'unité centrale de traitement [UCT]
  • G06F 9/54 - Communication interprogramme

91.

SOFTWARE DEVELOPMENT QUALITY ASSESSMENT

      
Numéro d'application US2023030752
Numéro de publication 2024/058913
Statut Délivré - en vigueur
Date de dépôt 2023-08-22
Date de publication 2024-03-21
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Fanning, Michael C.
  • Mukherjee, Suvam
  • Gonzalez, Danielle Nicole
  • Faucon, Christopher Michael Henry
  • Prakash, Pragya

Abrégé

Static analysis of a code base is expanded beyond finding faults to also find code instances where a particular fault could have occurred but did not. A conformance count reflects code portions that satisfy a specified coding rule per static analysis, and a nonconformance count reflects code portions that do not satisfy the coding rule. Various metrics computed from the conformance count and nonconformance count drive software development quality assessments. For example, bugs or bug categories may be prioritized for developer attention, static analysis tools are evaluated based on the metrics, to reduce noise by eliminating low-value bug alerts. Particular areas of expertise of developers and developer groups are objectively identified. Source code editors are enhanced to provide specific recommendations in context. Other quality enhancements are also provided.

Classes IPC  ?

92.

NEAR-EYE DISPLAY SYSTEMS UTILIZING AN ARRAY OF PROJECTORS

      
Numéro d'application US2023030756
Numéro de publication 2024/058914
Statut Délivré - en vigueur
Date de dépôt 2023-08-22
Date de publication 2024-03-21
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Kollin, Joel Steven
  • Georgiou, Andreas
  • Chatterjee, Ishan
  • Kress, Bernard Charles
  • Pace, Maria Esther
  • Possiwan, Mario

Abrégé

The present disclosure describes near-eye display systems including an array of projectors and a one-dimensional exit pupil expander. The array of projectors can be arranged along a first dimension and can output image light towards an input coupler within a waveguide that provides one-dimensional exit pupil expansion. In some implementations, arrays of monochromatic projectors are implemented and arranged in offset columns. The input coupler in-couples the image light from the array of projectors into a TIR path within the waveguide. Different optical elements, including diffractive and reflective optics, may be implemented as the input coupler. The image light travels within the waveguide until it interacts with an output coupler. Upon interaction with the output coupler, the image light is expanded in a second dimension transverse to the first dimension and is coupled out of the waveguide.

Classes IPC  ?

  • G02B 27/01 - Dispositifs d'affichage "tête haute"
  • G02B 27/00 - Systèmes ou appareils optiques non prévus dans aucun des groupes ,

93.

CLASSIFICATION USING A MACHINE LEARNING MODEL TRAINED WITH TRIPLET LOSS

      
Numéro d'application US2023030757
Numéro de publication 2024/058915
Statut Délivré - en vigueur
Date de dépôt 2023-08-22
Date de publication 2024-03-21
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Sharma, Pramod Kumar
  • Martinez, Andy Daniel
  • Du, Liang
  • Abraham, Robin
  • Thakur, Saurabh Chandrakant

Abrégé

A machine learning model trained with a triplet loss function classifies input strings into one of multiple hierarchical categories. The machine learning model is pre-trained using masking language modeling on a corpus of unlabeled strings. The machine learning module includes an attention-based bi-directional transformer layer. Following initial training, the machine learning model is refined by additional training with a loss function that includes cross-entropy loss and triplet loss. This provides a deep learning solution to classify input strings into one or more hierarchical categories. Embeddings generated from inputs to the machine learning model capture language similarities that can be visualized in a cartesian plane where strings with similar meanings are grouped together.

Classes IPC  ?

94.

OPTICAL ARRAY PANEL TRANSLATION

      
Numéro d'application US2023030758
Numéro de publication 2024/058916
Statut Délivré - en vigueur
Date de dépôt 2023-08-22
Date de publication 2024-03-21
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s) Yang, Long

Abrégé

A head-wearable display device includes a display panel to emit display light. An optical array panel is positioned along an optical path of the display light emitted by the display panel, and configured to redirect the display light toward an eyebox. An eye tracking system estimates a current pupil position of a user eye relative to the head-wearable display device. An actuator translates a position of the optical array panel relative to the display panel to move a position of the eyebox toward the current pupil position of the user eye.

Classes IPC  ?

  • G02B 27/00 - Systèmes ou appareils optiques non prévus dans aucun des groupes ,
  • G02B 27/01 - Dispositifs d'affichage "tête haute"
  • G02B 26/08 - Dispositifs ou dispositions optiques pour la commande de la lumière utilisant des éléments optiques mobiles ou déformables pour commander la direction de la lumière
  • G06F 3/01 - Dispositions d'entrée ou dispositions d'entrée et de sortie combinées pour l'interaction entre l'utilisateur et le calculateur

95.

NON-DISRUPTIVE SERVICING OF COMPONENTS OF A USER MODE PROCESS

      
Numéro d'application US2023030764
Numéro de publication 2024/058919
Statut Délivré - en vigueur
Date de dépôt 2023-08-22
Date de publication 2024-03-21
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s)
  • Retzlaff, Robert Tyler
  • Cardona, Omar
  • Zhou, Jie
  • Malloy, Dmitry

Abrégé

Examples of the present disclosure describe systems and methods for the non-disruptive servicing of components of a user mode process. In examples, a user mode process comprises multiple components, each encapsulating a distinct piece of functionality. A replacement component is loaded and initialized. The replacement component is validated to ensure that the required dependencies of the replacement component are satisfied by the other components of the user mode process. The component to be serviced and the components having dependencies on the component to be serviced are suspended to enable a snapshot of the runtime state of the component to be serviced to be captured. The runtime state is copied to the replacement component and the components having dependencies on the component to be serviced are updated to reference the replacement component. The replacement component is executed and the suspended components are resumed. The component to be serviced is unloaded.

Classes IPC  ?

  • G06F 9/46 - Dispositions pour la multiprogrammation
  • G06F 8/656 - Mises à jour pendant le fonctionnement
  • G06F 8/70 - Maintenance ou gestion de logiciel
  • G06F 9/445 - Chargement ou démarrage de programme
  • G06F 9/48 - Lancement de programmes; Commutation de programmes, p.ex. par interruption
  • G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p.ex. en utilisant différentes séquences d'opérations aboutissant au même résultat

96.

LOGGING CACHE LINE LIFETIME HINTS WHEN RECORDING BIT-ACCURATE TRACE

      
Numéro d'application 18548320
Statut En instance
Date de dépôt 2022-03-21
Date de la première publication 2024-03-21
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s) Mola, Jordi

Abrégé

Logging cache line lifetime hints when recording an execution trace. A microprocessor detects occurrence of a first cache event that initiates a lifetime of a cache line within a memory cache, and initiates logging first trace information indicating a beginning of the lifetime of the cache line within the memory cache. Subsequently, the microprocessor detects occurrence of a second cache event that ends the lifetime of the cache line within the memory cache. Based on detecting the second cache event, the microprocessor initiates logging second trace information indicating an ending of the lifetime of the cache line within the memory cache.

Classes IPC  ?

  • G06F 12/128 - Commande de remplacement utilisant des algorithmes de remplacement adaptée aux systèmes de mémoires cache multidimensionnelles, p.ex. associatives d’ensemble, à plusieurs mémoires cache, multi-ensembles ou multi-niveaux
  • G06F 12/0895 - Mémoires cache caractérisées par leur organisation ou leur structure de parties de mémoires cache, p.ex. répertoire ou matrice d’étiquettes

97.

MEMORY ADDRESS COMPRESSION WITHIN AN EXECUTION TRACE

      
Numéro d'application 18548318
Statut En instance
Date de dépôt 2022-03-21
Date de la première publication 2024-03-21
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s) Mola, Jordi

Abrégé

Compressing memory addresses within an execution trace via reference to a translation lookaside buffer (TLB) entry. A microprocessor identifies a TLB entry within a TLB slot, the TLB entry mapping a virtual memory page to a physical memory page. The microprocessor initiates logging of the TLB entry by initiating logging of at least a virtual address of the virtual memory page, and an identifier that uniquely identifies the TLB entry from among a plurality of live TLB entries. Subsequently, the microprocessor identifies a cache entry within a memory cache slot, the cache entry comprising a physical memory address corresponding to a cache line. The microprocessor initiates logging of the cache entry by matching a physical memory page identification portion of the physical memory address with the TLB entry, and then initiates logging of at least the identifier for the TLB entry and an offset portion.

Classes IPC  ?

  • G06F 12/1045 - Traduction d'adresses utilisant des moyens de traduction d’adresse associatifs ou pseudo-associatifs, p.ex. un répertoire de pages actives [TLB] associée à une mémoire cache de données
  • G06F 11/34 - Enregistrement ou évaluation statistique de l'activité du calculateur, p.ex. des interruptions ou des opérations d'entrée–sortie
  • G06F 12/0811 - Systèmes de mémoire cache multi-utilisateurs, multiprocesseurs ou multitraitement avec hiérarchies de mémoires cache multi-niveaux

98.

AUTOMATIC SUGGESTION OF VARIATION PARAMETERS & PRE-PACKAGED SYNTHETIC DATASETS

      
Numéro d'application 18514561
Statut En instance
Date de dépôt 2023-11-20
Date de la première publication 2024-03-21
Propriétaire MICROSOFT TECHNOLOGY LICENSING, LLC (USA)
Inventeur(s) Zargahi, Kamran

Abrégé

Various techniques are described for automatically suggesting variation parameters used to generate a tailored synthetic dataset to train a particular machine learning model. A seeding taxonomy associates a plurality of machine learning scenarios with corresponding subsets of variation parameters. A selected machine learning scenario is used to retrieve a corresponding subset of variation parameters associated with the selected machine learning scenario by the seeding taxonomy. The seeding taxonomy may be adaptable using a feedback loop that tracks selected variation parameters and updates the seeding taxonomy. The suggested variation parameters are presented as suggestions to assist users to identify and select relevant variation parameters faster and more efficiently. Further embodiments relate to pre-packaging synthetic datasets for common or anticipated machine learning scenarios. A user interface may present available packages of synthetic data for a selected industry sector and/or scenario, and a selected package may be made available for download.

Classes IPC  ?

  • G06F 9/50 - Allocation de ressources, p.ex. de l'unité centrale de traitement [UCT]
  • G06F 9/48 - Lancement de programmes; Commutation de programmes, p.ex. par interruption
  • G06F 9/54 - Communication interprogramme
  • G06F 16/9038 - Présentation des résultats des requêtes
  • G06F 16/906 - Groupement; Classement
  • G06F 16/907 - Recherche caractérisée par l’utilisation de métadonnées, p.ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
  • G06F 18/21 - Conception ou mise en place de systèmes ou de techniques; Extraction de caractéristiques dans l'espace des caractéristiques; Séparation aveugle de sources
  • G06F 18/214 - Génération de motifs d'entraînement; Procédés de Bootstrapping, p.ex. ”bagging” ou ”boosting”
  • G06F 18/24 - Techniques de classification
  • G06N 20/00 - Apprentissage automatique
  • G06V 10/774 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p.ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]; Séparation aveugle de source méthodes de Bootstrap, p.ex. "bagging” ou “boosting”
  • G06V 10/96 - Gestion de tâches de reconnaissance d’images ou de vidéos
  • G06V 20/64 - Objets tridimensionnels
  • H04L 67/63 - Ordonnancement ou organisation du service des demandes d'application, p.ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises en acheminant une demande de service en fonction du contenu ou du contexte de la demande

99.

CLIFFORD NEURAL LAYERS FOR MULTIVECTOR SYSTEM MODELING

      
Numéro d'application 18087357
Statut En instance
Date de dépôt 2022-12-22
Date de la première publication 2024-03-21
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Brandstetter, Johannes
  • Welling, Max
  • Gupta, Jayesh Kumar

Abrégé

Generally discussed herein are devices, systems, and methods for machine learning (ML) modeling of a system that operates on a multivector object. A method includes receiving, by an ML model, the multivector object as an input that represents a state of the multivector system. The method includes operating, by the ML model and using a Clifford layer that includes neurons that implement a multivector kernel, on the multivector input to generate a multivector output that represents the state of the multivector system responsive to the multivector input.

Classes IPC  ?

  • G06N 3/063 - Réalisation physique, c. à d. mise en œuvre matérielle de réseaux neuronaux, de neurones ou de parties de neurone utilisant des moyens électroniques
  • G06N 20/10 - Apprentissage automatique utilisant des méthodes à noyaux, p.ex. séparateurs à vaste marge [SVM]

100.

PIXEL LUMINANCE FOR DIGITAL DISPLAY

      
Numéro d'application 18264948
Statut En instance
Date de dépôt 2022-02-10
Date de la première publication 2024-03-21
Propriétaire Microsoft Technology Licensing, LLC (USA)
Inventeur(s)
  • Zheng, Ying
  • Morris, Matthew D.
  • Gupta, Vasudha
  • Paik, Younghun

Abrégé

A digital display includes a plurality of pixel rows. For each pixel row, the digital display includes an EM gate driver configured to supply the pixel row with a luminance-controlling signal during each of a plurality of image frames. A luminance controller is configured to instruct the EM gate drivers to supply a pulse-width modulated signal to the plurality of pixel rows. Some pixel rows are supplied with a pulse-width modulated signal starting with an on pulse, and some pixel rows are supplied with a pulse-width modulated signal starting with an off pulse, on the same or different image frames.

Classes IPC  ?

  • G09G 3/32 - Dispositions ou circuits de commande présentant un intérêt uniquement pour l'affichage utilisant des moyens de visualisation autres que les tubes à rayons cathodiques pour la présentation d'un ensemble de plusieurs caractères, p.ex. d'une page, en composant l'ensemble par combinaison d'éléments individuels disposés en matrice utilisant des sources lumineuses commandées utilisant des panneaux électroluminescents semi-conducteurs, p.ex. utilisant des diodes électroluminescentes [LED]
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