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公开(公告)号：US11443645B2
公开(公告)日：2022-09-13
申请号：US16688172
申请日：2019-11-19
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： James R. Kozloski , Shikhar Kwatra , Rosanna S. Mannan , Emily A. Ray
Abstract: A reward learning system includes a user interface configured to receive modes of user information related to a state of the user. A cognitive computing system includes a reward system. The reward system includes a dynamically upgraded profile model of the user which is updated in accordance with the user information related to the state. The reward system is updated by machine learning employing feedback from user responses measured by the user interface and searched information by the cognitive computing system. The reward system includes an increasing reward protocol based on learned user preferences and responses and rewarded in accordance with user achievements.
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公开(公告)号：US20200150181A1
公开(公告)日：2020-05-14
申请号：US16189295
申请日：2018-11-13
Applicant: International Business Machines Corporation
Inventor： Emily A. Ray , Emmanuel Yashchin , Peilin Song , Kevin G. Stawiasz , Barry Linder , Alan Weger , Keith A. Jenkins , Raphael P. Robertazzi , Franco Stellari , James Stathis
IPC: G01R31/3193 , G01R31/319
Abstract: Methods and systems of detecting chip degradation are described. A processor may execute a test on a device at a first time, where the test includes executable instructions for the device to execute a task under specific conditions relating to a performance attribute. The processor may receive performance data indicating a set of outcomes from the task executed by the device during the test. The processor may determine a first value of a parameter of the performance attribute based on the identified subset. The processor may compare the first value with a second value of the parameter of the performance attribute. The second value is based on an execution of the test on the device at a second time. The processor may determine a degradation status of the device based on the comparison of the first value with the second value.
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公开(公告)号：US20190333155A1
公开(公告)日：2019-10-31
申请号：US15964856
申请日：2018-04-27
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： Karthikeyan Natesan Ramamurthy , Emily A. Ray , Dennis Wei , Gigi Y.C. Yuen-Reed
Abstract: A method, computer system, and a computer program product for generating and reporting a plurality of health insurance cost predictions via private transfer learning is provided. The present invention may include retrieving a set of source data, and a set of target data. The present invention may then include creating and anonymizing a plurality of source data sets, and at least one target data set. The present invention may further include generating one or more source learner models, and a target learner model. The present invention may then include combining the one or more generated source learner models and the generated target learner model to generate a transfer learner. The present invention may further include generating a prediction based on the generated transfer learner.
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公开(公告)号：US20180315326A1
公开(公告)日：2018-11-01
申请号：US15497709
申请日：2017-04-26
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： James R. Kozloski , Shikhar Kwatra , Rosanna S. Mannan , Emily A. Ray
Abstract: A reward learning system includes a user interface configured to receive modes of user information related to a state of the user. A cognitive computing system includes a reward system. The reward system includes a dynamically upgraded profile model of the user which is updated in accordance with the user information related to the state. The reward system is updated by machine learning employing feedback from user responses measured by the user interface and searched information by the cognitive computing system. The reward system includes an increasing reward protocol based on learned user preferences and responses and rewarded in accordance with user achievements.
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公开(公告)号：US10102090B2
公开(公告)日：2018-10-16
申请号：US15156136
申请日：2016-05-16
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： Keith A. Jenkins , Barry P. Linder , Emily A. Ray , Raphael P. Robertazzi , Peilin Song , James H. Stathis , Kevin G. Stawiasz , Franco Stellari , Alan J. Weger , Emmanuel Yashchin
IPC: G06F11/00 , G06F11/22 , G06F11/263
Abstract: A method and system are provided for chip testing. The method includes ascertaining a baseline for a functioning chip with no stress history by performing a non-destructive test procedure on the functioning chip. The method further includes repeating the test procedure on a chip under test using a threshold derived from the baseline as a reference point to determine a stress history of the chip under test. The test procedure includes ordering each of a plurality of functional patterns by a respective minimum operating period corresponding thereto, ranking each pattern based on at least one preceding available pattern to provide a plurality of pattern ranks, and calculating a sum by summing the pattern ranks. The sum calculated by the ascertaining step is designated as the baseline, and the sum calculated by the repeating step is compared to the threshold to determine the stress history of the chip under test.
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Patent Agency Ranking
公开(公告)号：US20200090534A1
公开(公告)日：2020-03-19
申请号：US16688172
申请日：2019-11-19
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： James R. Kozloski , Shikhar Kwatra , Rosanna S. Mannan , Emily A. Ray
Abstract: A reward learning system includes a user interface configured to receive modes of user information related to a state of the user. A cognitive computing system includes a reward system. The reward system includes a dynamically upgraded profile model of the user which is updated in accordance with the user information related to the state. The reward system is updated by machine learning employing feedback from user responses measured by the user interface and searched information by the cognitive computing system. The reward system includes an increasing reward protocol based on learned user preferences and responses and rewarded in accordance with user achievements.
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公开(公告)号：US10559215B2
公开(公告)日：2020-02-11
申请号：US15497709
申请日：2017-04-26
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： James R. Kozloski , Shikhar Kwatra , Rosanna S. Mannan , Emily A. Ray
Abstract: A reward learning system includes a user interface configured to receive modes of user information related to a state of the user. A cognitive computing system includes a reward system. The reward system includes a dynamically upgraded profile model of the user which is updated in accordance with the user information related to the state. The reward system is updated by machine learning employing feedback from user responses measured by the user interface and searched information by the cognitive computing system. The reward system includes an increasing reward protocol based on learned user preferences and responses and rewarded in accordance with user achievements.
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公开(公告)号：US10552278B2
公开(公告)日：2020-02-04
申请号：US16035032
申请日：2018-07-13
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： Keith A. Jenkins , Barry P. Linder , Emily A. Ray , Raphael P. Robertazzi , Peilin Song , James H. Stathis , Kevin G. Stawiasz , Franco Stellari , Alan J. Weger , Emmanuel Yashchin
IPC: G06F11/00 , G06F11/22 , G06F11/24 , G06F11/263
Abstract: A method and system are provided for chip testing. The method includes selectively deploying a chip for future use or discarding the chip to prevent the future use, responsive to a stress history of the chip determined using a non-destructive test procedure. The test procedure includes ordering each of a plurality of functional patterns by a respective minimum operating period corresponding thereto. The test procedure further includes ranking each of the plurality of patterns based on at least one preceding available pattern to provide a plurality of pattern ranks. The test procedure also includes calculating a sum by summing the plurality of pattern ranks. The sum calculated during an initial performance of the test procedure is designated as a baseline, and the sum calculated during a subsequent performance of the test procedure is compared to a threshold derived from the baseline to determine the stress history of the chip.
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公开(公告)号：US20180315327A1
公开(公告)日：2018-11-01
申请号：US15808256
申请日：2017-11-09
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： James R. Kozloski , Shikhar Kwatra , Rosanna S. Mannan , Emily A. Ray
Abstract: A reward learning system includes a user interface configured to receive modes of user information related to a state of the user. A cognitive computing system includes a reward system. The reward system includes a dynamically upgraded profile model of the user which is updated in accordance with the user information related to the state. The reward system is updated by machine learning employing feedback from user responses measured by the user interface and searched information by the cognitive computing system. The reward system includes an increasing reward protocol based on learned user preferences and responses and rewarded in accordance with user achievements.
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公开(公告)号：US11244013B2
公开(公告)日：2022-02-08
申请号：US15995653
申请日：2018-06-01
Applicant: International Business Machines Corporation
Inventor： Mary E. Helander , Emily A. Ray , Nizar Lethif , Joana Sofia Branquinho Teresa Maria , Kush R. Varshney , Hemank Lamba
IPC: G06F7/00 , G06F16/951 , G06F16/28 , G06F16/33 , G06F16/2457
Abstract: The system, method, and computer program product are disclosed that track the evolution of a network over time through the analysis of media corpora associated with nodes of the network at each time slice. The media corpora may be analyzed to generate word clusters for each time slice that are then compared across time slices to determine how the network has evolved. The evolution may be tracked by determining the similarity of each word cluster of a particular time slice to each word cluster of another time slice. The similarity may be measured by a similarity score for each comparison that may be combined to determine an overall similarity of the network between the two time slices.
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