Patents by Inventor Andrey Kolobov
Andrey Kolobov has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20220358171Abstract: The technology described herein builds an optimal refresh schedule by minimizing a cost function constrained by an available refresh bandwidth. The cost function receives an importance score for a content item and a change rate for the content item as input in order to optimize the schedule. The cost function is considered optimized when a refresh schedule is found that minimizes the cost while using the available bandwidth and no more. The technology can build an optimized schedule to refresh content with incomplete change data, content with complete change data, or a mixture of content with and without complete change data. It can also re-learn content item change rates from its own schedule execution history and re-compute the refresh schedule, ensuring that this schedule takes into account the latest trends in content item updates.Type: ApplicationFiled: July 1, 2022Publication date: November 10, 2022Inventors: Andrey KOLOBOV, Cheng LU, Eric J. HORVITZ, Yuval PERES
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Patent number: 11379539Abstract: The technology described herein builds an optimal refresh schedule by minimizing a cost function constrained by an available refresh bandwidth. The cost function receives an importance score for a content item and a change rate for the content item as input in order to optimize the schedule. The cost function is considered optimized when a refresh schedule is found that minimizes the cost while using the available bandwidth and no more. The technology can build an optimized schedule to refresh content with incomplete change data, content with complete change data, or a mixture of content with and without complete change data. It can also re-learn content item change rates from its own schedule execution history and re-compute the refresh schedule, ensuring that this schedule takes into account the latest trends in content item updates.Type: GrantFiled: May 22, 2019Date of Patent: July 5, 2022Assignee: MICROSOFT TECHNOLOGY LICENSING, LLCInventors: Andrey Kolobov, Cheng Lu, Eric J. Horvitz, Yuval Peres
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Patent number: 10909969Abstract: Domain-specific language understanding models that may be built, tested and improved quickly and efficiently are provided. Methods, systems and devices are provided that enable a developer to build user intent detection models, language entity extraction models, and language entity resolution models quickly and without specialized machine learning knowledge. These models may be built and implemented via single model systems that enable the models to be built in isolation or in an end-to-end pipeline system that enables the models to be built and improved in a simultaneous manner.Type: GrantFiled: September 25, 2019Date of Patent: February 2, 2021Assignee: Microsoft Technology Licensing, LLCInventors: Jason Douglas Williams, Nobal Bikram Niraula, Pradeep Dasigi, Aparna Lakshmiratan, Geoffrey G. Zweig, Andrey Kolobov, Carlos Garcia Jurado Suarez, David Maxwell Chickering
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Publication number: 20200372084Abstract: The technology described herein builds an optimal refresh schedule by minimizing a cost function constrained by an available refresh bandwidth. The cost function receives an importance score for a content item and a change rate for the content item as input in order to optimize the schedule. The cost function is considered optimized when a refresh schedule is found that minimizes the cost while using the available bandwidth and no more. The technology can build an optimized schedule to refresh content with incomplete change data, content with complete change data, or a mixture of content with and without complete change data. It can also re-learn content item change rates from its own schedule execution history and re-compute the refresh schedule, ensuring that this schedule takes into account the latest trends in content item updates.Type: ApplicationFiled: May 22, 2019Publication date: November 26, 2020Inventors: Andrey KOLOBOV, Cheng LU, Eric J. HORVITZ, Yuval PERES
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Publication number: 20200020317Abstract: Domain-specific language understanding models that may be built, tested and improved quickly and efficiently are provided. Methods, systems and devices are provided that enable a developer to build user intent detection models, language entity extraction models, and language entity resolution models quickly and without specialized machine learning knowledge. These models may be built and implemented via single model systems that enable the models to be built in isolation or in an end-to-end pipeline system that enables the models to be built and improved in a simultaneous manner.Type: ApplicationFiled: September 25, 2019Publication date: January 16, 2020Applicant: Microsoft Technology Licensing, LLCInventors: Jason Douglas WILLIAMS, Nobal Bikram NIRAULA, Pradeep DASIGI, Aparna LAKSHMIRATAN, Geoffrey G. ZWEIG, Andrey KOLOBOV, Carlos GARCIA JURADO SUAREZ, David Maxwell CHICKERING
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Patent number: 10460720Abstract: Domain-specific language understanding models that may be built, tested and improved quickly and efficiently are provided. Methods, systems and devices are provided that enable a developer to build user intent detection models, language entity extraction models, and language entity resolution models quickly and without specialized machine learning knowledge. These models may be built and implemented via single model systems that enable the models to be built in isolation or in an end-to-end pipeline system that enables the models to be built and improved in a simultaneous manner.Type: GrantFiled: April 3, 2015Date of Patent: October 29, 2019Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC.Inventors: Jason Douglas Williams, Nobal Bikram Niraula, Pradeep Dasigi, Aparna Lakshmiratan, Geoffrey G. Zweig, Andrey Kolobov, Carlos Garcia Jurado Suarez, David Maxwell Chickering
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Patent number: 9714831Abstract: Various technologies pertaining to dynamically identifying travel segments to be taken by a traveler traveling in a region are described herein, where observations about travel segments in the region are sparse and subject to alteration. A computer-implemented graph can be loaded into a memory, where the computer-implemented graph is representative of the region. The computer-implemented graph includes nodes that represent locations in the region and edges that represent travel segments of the region, where the edges have costs assigned thereto, and further where there is a defined statistical relationship between the costs. When an observation about a travel path is received, using the computer-implemented graph, inferences can be made about costs of traversing other travel paths in the region.Type: GrantFiled: July 7, 2014Date of Patent: July 25, 2017Assignee: Microsoft Technology Licensing, LLCInventors: Ashish Kapoor, Debadeepta Dey, Andrey Kolobov, Semiha Ece Kamar Eden, Richard Caruana, Eric Horvitz
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Publication number: 20160196820Abstract: Domain-specific language understanding models that may be built, tested and improved quickly and efficiently are provided. Methods, systems and devices are provided that enable a developer to build user intent detection models, language entity extraction models, and language entity resolution models quickly and without specialized machine learning knowledge. These models may be built and implemented via single model systems that enable the models to be built in isolation or in an end-to-end pipeline system that enables the models to be built and improved in a simultaneous manner.Type: ApplicationFiled: April 3, 2015Publication date: July 7, 2016Applicant: Microsoft Technology Licensing, LLC.Inventors: Jason Douglas Williams, Nobal Bikram Niraula, Pradeep Dasigi, Aparna Lakshmiratan, Geoffrey G. Zweig, Andrey Kolobov, Carlos Garcia Jurado Suarez, David Maxwell Chickering
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Publication number: 20160003620Abstract: Various technologies pertaining to dynamically identifying travel segments to be taken by a traveler traveling in a region are described herein, where observations about travel segments in the region are sparse and subject to alteration. A computer-implemented graph can be loaded into a memory, where the computer-implemented graph is representative of the region. The computer-implemented graph includes nodes that represent locations in the region and edges that represent travel segments of the region, where the edges have costs assigned thereto, and further where there is a defined statistical relationship between the costs. When an observation about a travel path is received, using the computer-implemented graph, inferences can be made about costs of traversing other travel paths in the region.Type: ApplicationFiled: July 7, 2014Publication date: January 7, 2016Inventors: Ashish Kapoor, Debadeepta Dey, Andrey Kolobov, Semiha Ece Kamar Eden, Richard Caruana, Eric Horvitz