Patents by Inventor James Ezick
James Ezick 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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Patent number: 11899740Abstract: We present the architecture of a high-performance constraint solver R-Solve that extends the gains made in SAT performance over the past fifteen years on static decision problems to problems that require on-the-fly adaptation, solution space exploration and optimization. R-Solve facilitates collaborative parallel solving and provides an efficient system for unrestricted incremental solving via Smart Repair. R-Solve can address problems in dynamic planning and constrained optimization involving complex logical and arithmetic constraints.Type: GrantFiled: December 7, 2020Date of Patent: February 13, 2024Assignee: QUALCOMM IncorporatedInventors: James Ezick, Thomas Henretty, Chanseok Oh, Jonathan Springer
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Patent number: 11797894Abstract: In a system for enabling configuration of an ensemble of several solvers, such that the ensemble can efficiently solve a constraint problem, for each one of several candidate configurations, an array of scores is computed. The array corresponds to a statistical parameter related to a problem solution, and the computation is based on, at least in part, a set of features associated with the problem. One candidate configuration is assigned to a solver, and based on the array of scores associated with that candidate configuration the same or a different candidate configuration is assigned to a another solver. A system for dynamically reconfiguring an ensemble of solvers obtains runtime data from several solvers, and a new configuration is determined by applying a machine learning and/or heuristic analysis procedure to the runtime data. The configuration of a solver may be updated according to the new configuration while that solver is running.Type: GrantFiled: November 16, 2020Date of Patent: October 24, 2023Assignee: QUALCOMM IncorporatedInventors: James Ezick, Jonathan Springer, Nicolas T. Vasilache
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Systems and methods for configuring system memory for extraction of latent information from big data
Patent number: 11704332Abstract: A system for extracting latent information from data includes obtaining or generating components of the data, where the data components include scores indicating how the component relates to the data. Memory is allocated for the components and the components are stored in the allocated memory. The components are then transformed into documents using a suitable transformation function, and the documents are analyzed using natural language processing, to extract latent information contained in the data.Type: GrantFiled: July 8, 2021Date of Patent: July 18, 2023Assignee: RESERVOIR LABS INCInventors: James Ezick, Thomas Henretty, Richard A. Lethin -
Patent number: 11520856Abstract: A system for performing tensor decomposition in a selective expansive and/or recursive manner, a tensor is decomposed into a specified number of components, and one or more tensor components are selected for further decomposition. For each selected component, the significant elements thereof are identified, and using the indices of the significant elements a sub-tensor is formed. In a subsequent iteration, each sub-tensor is decomposed into a respective specified number of components. Additional sub-tensors corresponding to the components generated in the subsequent iteration are formed, and these additional sub-tensors may be decomposed further in yet another iteration, until no additional components are selected. The mode of a sub-tensor can be decreased or increased prior to decomposition thereof. Components likely to reveal information about the data stored in the tensor can be selected for decomposition.Type: GrantFiled: November 2, 2020Date of Patent: December 6, 2022Assignee: Qualcomm IncorporatedInventors: Muthu M. Baskaran, David Bruns-Smith, James Ezick, Richard A. Lethin
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Patent number: 11481468Abstract: We present the architecture of a high-performance constraint solver R-Solve that extends the gains made in SAT performance over the past fifteen years on static decision problems to problems that require on-the-fly adaptation, solution space exploration and optimization. R-Solve facilitates collaborative parallel solving and provides an efficient system for unrestricted incremental solving via Smart Repair. R-Solve can address problems in dynamic planning and constrained optimization involving complex logical and arithmetic constraints.Type: GrantFiled: June 3, 2015Date of Patent: October 25, 2022Assignee: Qualcomm Technologies, Inc.Inventors: James Ezick, Thomas Henretty, Chanseok Oh, Jonathan Springer
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Patent number: 11481469Abstract: We present the architecture of a high-performance constraint solver R-Solve that extends the gains made in SAT performance over the past fifteen years on static decision problems to problems that require on-the-fly adaptation, solution space exploration and optimization. R-Solve facilitates collaborative parallel solving and provides an efficient system for unrestricted incremental solving via Smart Repair. R-Solve can address problems in dynamic planning and constrained optimization involving complex logical and arithmetic constraints.Type: GrantFiled: September 15, 2015Date of Patent: October 25, 2022Assignee: Qualcomm Technologies, Inc.Inventors: James Ezick, Thomas Henretty, Chanseok Oh, Jonathan Springer
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SYSTEMS AND METHODS FOR CONFIGURING SYSTEM MEMORY FOR EXTRACTION OF LATENT INFORMATION FROM BIG DATA
Publication number: 20220043827Abstract: A system for extracting latent information from data includes obtaining or generating components of the data, where the data components include scores indicating how the component relates to the data. Memory is allocated for the components and the components are stored in the allocated memory. The components are then transformed into documents using a suitable transformation function, and the documents are analyzed using natural language processing, to extract latent information contained in the data.Type: ApplicationFiled: July 8, 2021Publication date: February 10, 2022Inventors: James Ezick, Thomas Henretty, Richard A. Lethin -
Publication number: 20210334331Abstract: We present the architecture of a high-performance constraint solver R-Solve that extends the gains made in SAT performance over the past fifteen years on static decision problems to problems that require on-the-fly adaptation, solution space exploration and optimization. R-Solve facilitates collaborative parallel solving and provides an efficient system for unrestricted incremental solving via Smart Repair. R-Solve can address problems in dynamic planning and constrained optimization involving complex logical and arithmetic constraints.Type: ApplicationFiled: December 7, 2020Publication date: October 28, 2021Inventors: James Ezick, Thomas Henretty, Chanseok Oh, Jonathan Springer
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Publication number: 20210294876Abstract: A system for performing tensor decomposition in a selective expansive and/or recursive manner, a tensor is decomposed into a specified number of components, and one or more tensor components are selected for further decomposition. For each selected component, the significant elements thereof are identified, and using the indices of the significant elements a sub-tensor is formed. In a subsequent iteration, each sub-tensor is decomposed into a respective specified number of components. Additional sub-tensors corresponding to the components generated in the subsequent iteration are formed, and these additional sub-tensors may be decomposed further in yet another iteration, until no additional components are selected. The mode of a sub-tensor can be decreased or increased prior to decomposition thereof. Components likely to reveal information about the data stored in the tensor can be selected for decomposition.Type: ApplicationFiled: November 2, 2020Publication date: September 23, 2021Inventors: Muthu Manikandan Baskaran, David Bruns-Smith, James Ezick, Richard A. Lethin
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Systems and methods for configuring system memory for extraction of latent information from big data
Patent number: 11074269Abstract: A system for extracting latent information from data includes obtaining or generating components of the data, where the data components include scores indicating how the component relates to the data. Memory is allocated for the components and the components are stored in the allocated memory. The components are then transformed into documents using a suitable transformation function, and the documents are analyzed using natural language processing, to extract latent information contained in the data.Type: GrantFiled: January 10, 2019Date of Patent: July 27, 2021Assignee: Reservoir Labs, Inc.Inventors: James Ezick, Thomas Henretty, Richard A. Lethin -
Patent number: 10860945Abstract: We present the architecture of a high-performance constraint solver R-Solve that extends the gains made in SAT performance over the past fifteen years on static decision problems to problems that require on-the-fly adaptation, solution space exploration and optimization. R-Solve facilitates collaborative parallel solving and provides an efficient system for unrestricted incremental solving via Smart Repair. R-Solve can address problems in dynamic planning and constrained optimization involving complex logical and arithmetic constraints.Type: GrantFiled: September 15, 2015Date of Patent: December 8, 2020Assignee: Reservoir Labs, Inc.Inventors: James Ezick, Thomas Henretty, Chanseok Oh, Jonathan Springer
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Patent number: 10839297Abstract: In a system for enabling configuration of an ensemble of several solvers, such that the ensemble can efficiently solve a constraint problem, for each one of several candidate configurations, an array of scores is computed. The array corresponds to a statistical parameter related to a problem solution, and the computation is based on, at least in part, a set of features associated with the problem. One candidate configuration is assigned to a solver, and based on the array of scores associated with that candidate configuration the same or a different candidate configuration is assigned to a another solver. A system for dynamically reconfiguring an ensemble of solvers obtains runtime data from several solvers, and a new configuration is determined by applying a machine learning and/or heuristic analysis procedure to the runtime data. The configuration of a solver may be updated according to the new configuration while that solver is running.Type: GrantFiled: June 8, 2017Date of Patent: November 17, 2020Assignee: Reservoir Labs, Inc.Inventors: James Ezick, Jonathan Springer, Nicolas T. Vasilache
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Patent number: 10824693Abstract: A system for performing tensor decomposition in a selective expansive and/or recursive manner, a tensor is decomposed into a specified number of components, and one or more tensor components are selected for further decomposition. For each selected component, the significant elements thereof are identified, and using the indices of the significant elements a sub-tensor is formed. In a subsequent iteration, each sub-tensor is decomposed into a respective specified number of components. Additional sub-tensors corresponding to the components generated in the subsequent iteration are formed, and these additional sub-tensors may be decomposed further in yet another iteration, until no additional components are selected. The mode of a sub-tensor can be decreased or increased prior to decomposition thereof. Components likely to reveal information about the data stored in the tensor can be selected for decomposition.Type: GrantFiled: December 12, 2016Date of Patent: November 3, 2020Assignee: Reservoir Labs, Inc.Inventors: Muthu M. Baskaran, David Bruns-Smith, James Ezick, Richard A. Lethin
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SYSTEMS AND METHODS FOR CONFIGURING SYSTEM MEMORY FOR EXTRACTION OF LATENT INFORMATION FROM BIG DATA
Publication number: 20190317945Abstract: A system for extracting latent information from data includes obtaining or generating components of the data, where the data components include scores indicating how the component relates to the data. Memory is allocated for the components and the components are stored in the allocated memory. The components are then transformed into documents using a suitable transformation function, and the documents are analyzed using natural language processing, to extract latent information contained in the data.Type: ApplicationFiled: January 10, 2019Publication date: October 17, 2019Inventors: James Ezick, Thomas Henretty, Richard A. Lethin -
Patent number: 10402747Abstract: We present the architecture of a high-performance constraint solver R-Solve that extends the gains made in SAT performance over the past fifteen years on static decision problems to problems that require on-the-fly adaptation, solution space exploration and optimization. R-Solve facilitates collaborative parallel solving and provides an efficient system for unrestricted incremental solving via Smart Repair. R-Solve can address problems in dynamic planning and constrained optimization involving complex logical and arithmetic constraints.Type: GrantFiled: June 3, 2015Date of Patent: September 3, 2019Assignee: Reservoir Labs, Inc.Inventors: James Ezick, Thomas Henretty, Chanseok Oh, Jonathan Springer
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Patent number: 9684865Abstract: In a system for enabling configuration of an ensemble of several solvers, such that the ensemble can efficiently solve a constraint problem, for each one of several candidate configurations, an array of scores is computed. The array corresponds to a statistical parameter related to a problem solution, and the computation is based on, at least in part, a set of features associated with the problem. One candidate configuration is assigned to a solver, and based on the array of scores associated with that candidate configuration the same or a different candidate configuration is assigned to a another solver. A system for dynamically reconfiguring an ensemble of solvers obtains runtime data from several solvers, and a new configuration is determined by applying a machine learning and/or heuristic analysis procedure to the runtime data. The configuration of a solver may be updated according to the new configuration while that solver is running.Type: GrantFiled: June 5, 2013Date of Patent: June 20, 2017Assignee: Significs and Elements, LLCInventors: James Ezick, Jonathan Springer, Nicolas T. Vasilache
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Publication number: 20170168991Abstract: A system for performing tensor decomposition in a selective expansive and/or recursive manner, a tensor is decomposed into a specified number of components, and one or more tensor components are selected for further decomposition. For each selected component, the significant elements thereof are identified, and using the indices of the significant elements a sub-tensor is formed. In a subsequent iteration, each sub-tensor is decomposed into a respective specified number of components. Additional sub-tensors corresponding to the components generated in the subsequent iteration are formed, and these additional sub-tensors may be decomposed further in yet another iteration, until no additional components are selected. The mode of a sub-tensor can be decreased or increased prior to decomposition thereof. Components likely to reveal information about the data stored in the tensor can be selected for decomposition.Type: ApplicationFiled: December 12, 2016Publication date: June 15, 2017Inventors: Muthu M. Baskaran, David Bruns-Smith, James Ezick, Richard A. Lethin
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Publication number: 20160034825Abstract: We present the architecture of a high-performance constraint solver R-Solve that extends the gains made in SAT performance over the past fifteen years on static decision problems to problems that require on-the-fly adaptation, solution space exploration and optimization. R-Solve facilitates collaborative parallel solving and provides an efficient system for unrestricted incremental solving via Smart Repair. R-Solve can address problems in dynamic planning and constrained optimization involving complex logical and arithmetic constraints.Type: ApplicationFiled: September 15, 2015Publication date: February 4, 2016Inventors: James Ezick, Thomas Henretty, Chanseok Oh, Jonathan Springer
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Publication number: 20160004967Abstract: We present the architecture of a high-performance constraint solver R-Solve that extends the gains made in SAT performance over the past fifteen years on static decision problems to problems that require on-the-fly adaptation, solution space exploration and optimization. R-Solve facilitates collaborative parallel solving and provides an efficient system for unrestricted incremental solving via Smart Repair. R-Solve can address problems in dynamic planning and constrained optimization involving complex logical and arithmetic constraints.Type: ApplicationFiled: September 15, 2015Publication date: January 7, 2016Inventors: James Ezick, Thomas Henretty, Chanseok Oh, Jonathan Springer
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Publication number: 20150379403Abstract: We present the architecture of a high-performance constraint solver R-Solve that extends the gains made in SAT performance over the past fifteen years on static decision problems to problems that require on-the-fly adaptation, solution space exploration and optimization. R-Solve facilitates collaborative parallel solving and provides an efficient system for unrestricted incremental solving via Smart Repair. R-Solve can address problems in dynamic planning and constrained optimization involving complex logical and arithmetic constraints.Type: ApplicationFiled: June 3, 2015Publication date: December 31, 2015Inventors: James Ezick, Thomas Henretty, Chanseok Oh, Jonathan Springer