Patents by Inventor Bradley Eck
Bradley Eck 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: 20240112066Abstract: A computer-implemented method, a computer program product, and a computer system for retraining a model in case of a drift in machine learning. A computer detects a drift in machine learning. A computer identifies in a database features and a response of a machine learning model. A computer determines a time window of the drift. A computer extracts, from the database, data of the features and the response in the time window. A computer determines whether extracted data is sufficient for retraining the machine learning model. A computer, in response to determining that the extracted data is not sufficient for retraining the machine learning model, interpolates one or more of the features for a predetermined future time horizon. A computer interpolates a response corresponding to one or more interpolated features. A computer retrains the machine learning model, using the one or more interpolated features and an interpolated response corresponding thereto.Type: ApplicationFiled: September 29, 2022Publication date: April 4, 2024Inventors: Amadou Ba, Venkata Sitaramagiridharganesh Ganapavarapu, Seshu Tirupathi, Bradley Eck
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Publication number: 20230177118Abstract: One or more systems, devices, computer program products and/or computer-implemented methods of use provided herein relate to training a learning model based on determined drift. A system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components can comprise a selection component that can select an ensemble of deep learning regressors, and an identification component that can identify drift among the ensemble. An analysis component can analyze uncertainty samplings from the ensemble to determine a time instant when drift occurred. A training component can train one or more deep learning models, such as of the deep learning regressors, based upon the identified drift.Type: ApplicationFiled: December 3, 2021Publication date: June 8, 2023Inventors: Amadou Ba, Venkata Sitaramagiridharganesh Ganapavarapu, Seshu Tirupathi, Bradley Eck
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Patent number: 11475332Abstract: A computer-implemented method, a computer program product, and a computer system for selecting predictions by models. A computer receives a request for a forecast of a dependent variable in a time domain, where the time domain includes first time periods that have normal labels due to normal predictor variable data and second time periods that have anomalous labels due to anomalous predictor variable data. The computer retrieves accuracy scores and robustness scores of models, where the accuracy scores indicate forecasting accuracy in the first time periods and the robustness scores indicate forecasting accuracy in the second time periods. For predictions in the first time period, the computer selects dependent variable values predicted by a first model that has highest values of the accuracy scores. For predictions in the second time periods, the computer selects dependent variable values predicted by a second model that has highest values of the robustness scores.Type: GrantFiled: July 12, 2020Date of Patent: October 18, 2022Assignee: International Business Machines CorporationInventors: Robert Gormally, Bradley Eck, Francesco Fusco, Mark Purcell, Seshu Tirupathi
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Publication number: 20220012609Abstract: A computer-implemented method, a computer program product, and a computer system for selecting predictions by models. A computer receives a request for a forecast of a dependent variable in a time domain, where the time domain includes first time periods that have normal labels due to normal predictor variable data and second time periods that have anomalous labels due to anomalous predictor variable data. The computer retrieves accuracy scores and robustness scores of models, where the accuracy scores indicate forecasting accuracy in the first time periods and the robustness scores indicate forecasting accuracy in the second time periods. For predictions in the first time period, the computer selects dependent variable values predicted by a first model that has highest values of the accuracy scores. For predictions in the second time periods, the computer selects dependent variable values predicted by a second model that has highest values of the robustness scores.Type: ApplicationFiled: July 12, 2020Publication date: January 13, 2022Inventors: Robert Gormally, Bradley Eck, Francesco Fusco, Mark Purcell, Seshu Tirupathi
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Patent number: 11087525Abstract: Embodiments for intelligent unsupervised learning of visual alphabets by one or more processors are described. A visual three-dimensional (3D) alphabet may be learned from one or more images using a machine learning operations. A set of 3D primitives representing the visual 3D alphabet may be provided.Type: GrantFiled: January 8, 2020Date of Patent: August 10, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Thanh Lam Hoang, Albert Akhriev, Ngoc Minh Tran, Bradley Eck, Tuan Dinh
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Publication number: 20210209833Abstract: Embodiments for intelligent unsupervised learning of visual alphabets by one or more processors are described. A visual three-dimensional (3D) alphabet may be learned from one or more images using a machine learning operations. A set of 3D primitives representing the visual 3D alphabet may be provided.Type: ApplicationFiled: January 8, 2020Publication date: July 8, 2021Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Thanh Lam HOANG, Albert AKHRIEV, Ngoc Minh TRAN, Bradley ECK, Tuan DINH
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Patent number: 11047722Abstract: A method for estimating a fluid flow velocity may include receiving, with a processing device, a plurality of observations corresponding to a concentration of a constituent of a flowing fluid mixture, and computing a final estimate of an average velocity of the flowing fluid mixture based at least in part on the observations, wherein the constituent is undergoing a chemical reaction and the computing implements a reactive transport model.Type: GrantFiled: December 17, 2013Date of Patent: June 29, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Bradley Eck, Sergiy Zhuk
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Patent number: 11010689Abstract: Techniques that facilitate semantic and time series analysis using machine learning are provided. In one example, a system includes a data analysis component, a prediction component and a learning component. The data analysis component that establishes one or more relationships between one or more elements of semantic data, including one or more time series identifiers, and one or more elements of time series data in a relationship database. The prediction component generates one or more advisory outputs, wherein generation of the one or more advisory outputs is performed in response to a trigger event. A learning component that determines the one or more relationships in the relationship database, wherein determination of the one or more relationships is based on information indicative of whether the advisory outputs satisfy a defined criterion.Type: GrantFiled: December 14, 2017Date of Patent: May 18, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Bradley Eck, Vincent Lonij, Pascal Pompey
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Patent number: 10970648Abstract: Techniques that facilitate semantic and time series analysis using machine learning are provided. In one example, a system includes a data analysis component, a prediction component and a learning component. The data analysis component that establishes one or more relationships between one or more elements of semantic data, including one or more time series identifiers, and one or more elements of time series data in a relationship database. The prediction component generates one or more advisory outputs, wherein generation of the one or more advisory outputs is performed in response to a trigger event, a learning component that determines the one or more relationships in the relationship database, wherein determination of the one or more relationships is based on information indicative of whether the advisory outputs satisfy a defined criterion.Type: GrantFiled: August 30, 2017Date of Patent: April 6, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Bradley Eck, Vincent Lonij, Pascal Pompey
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Patent number: 10782655Abstract: A sensor data fusion system includes a processor coupled to a plurality of sensors. The system is initialized by providing access to a data store storing at least one time series of sensor data; a semantic store storing semantic data including system variables, and relations between the system variables; and a mapping therebetween. A registration of a set of one or more variables of interest for which appropriate data is not available is obtained. An initially empty inference model is extended with the set of variables, to obtain an extended model. A request to observe a given one of the set of variables at a given timestamp is obtained. Responsive thereto, time series data for the set of registered variables is retrieved. The extended model is run with the retrieved data to obtain an estimate of the given one of the variables at the given timestamp.Type: GrantFiled: June 16, 2018Date of Patent: September 22, 2020Assignee: International Business Machines CorporationInventors: Bradley Eck, Francesco Fusco, Seshu Tirupathi
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Patent number: 10594817Abstract: A social network platform and method thereof for providing Internet of Things (I-o-T) devices with social behavior for communicating natural language (NL) text messages. An I-o-T device is provided with a social device application to form a unit capable of: reading free form NL messages, and responsively perform an action. The social device application generates NL text in response to reading a text message and/or in response to receiving readings from a set of sensors. Types of messages generated include messages for initiating social relationships with other devices which may communicate an acceptance/declination. The platform may be centralized with a server for ranking the importance of read messages based on the relationships and addressing NL text messages to other social units or groups of social units based on the relationships. The platform further enables direct messaging between social unit devices, brokering trust, and moderating information flow between devices.Type: GrantFiled: October 4, 2017Date of Patent: March 17, 2020Assignee: International Business Machines CorporationInventors: Vincent Lonij, Bradley Eck, Amadou Ba
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Patent number: 10587710Abstract: A social network platform and method thereof for providing Internet of Things (I-o-T) devices with social behavior for communicating natural language (NL) text messages. An I-o-T device is provided with a social device application to form a unit capable of: reading free form NL messages, and responsively perform an action. The social device application generates NL text in response to reading a text message and/or in response to receiving readings from a set of sensors. Types of messages generated include messages for initiating social relationships with other devices which may communicate an acceptance/declination. The platform may be centralized with a server for ranking the importance of read messages based on the relationships and addressing NL text messages to other social units or groups of social units based on the relationships. The platform further enables direct messaging between social unit devices, brokering trust, and moderating information flow between devices.Type: GrantFiled: November 9, 2017Date of Patent: March 10, 2020Assignee: International Business Machines CorporationInventors: Vincent Lonij, Bradley Eck, Amadou Ba
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Publication number: 20190384235Abstract: A sensor data fusion system includes a processor coupled to a plurality of sensors. The system is initialized by providing access to a data store storing at least one time series of sensor data; a semantic store storing semantic data including system variables, and relations between the system variables; and a mapping therebetween. A registration of a set of one or more variables of interest for which appropriate data is not available is obtained. An initially empty inference model is extended with the set of variables, to obtain an extended model. A request to observe a given one of the set of variables at a given timestamp is obtained. Responsive thereto, time series data for the set of registered variables is retrieved. The extended model is run with the retrieved data to obtain an estimate of the given one of the variables at the given timestamp.Type: ApplicationFiled: June 16, 2018Publication date: December 19, 2019Inventors: BRADLEY ECK, FRANCESCO FUSCO, SESHU TIRUPATHI
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Publication number: 20190104191Abstract: A social network platform and method thereof for providing Internet of Things (I-o-T) devices with social behavior for communicating natural language (NL) text messages. An I-o-T device is provided with a social device application to form a unit capable of: reading free form NL messages, and responsively perform an action. The social device application generates NL text in response to reading a text message and/or in response to receiving readings from a set of sensors. Types of messages generated include messages for initiating social relationships with other devices which may communicate an acceptance/declination. The platform may be centralized with a server for ranking the importance of read messages based on the relationships and addressing NL text messages to other social units or groups of social units based on the relationships. The platform further enables direct messaging between social unit devices, brokering trust, and moderating information flow between devices.Type: ApplicationFiled: October 4, 2017Publication date: April 4, 2019Inventors: Vincent Lonij, Bradley Eck, Amadou Ba
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Publication number: 20190104192Abstract: A social network platform and method thereof for providing Internet of Things (I-o-T) devices with social behavior for communicating natural language (NL) text messages. An I-o-T device is provided with a social device application to form a unit capable of: reading free form NL messages, and responsively perform an action. The social device application generates NL text in response to reading a text message and/or in response to receiving readings from a set of sensors. Types of messages generated include messages for initiating social relationships with other devices which may communicate an acceptance/declination. The platform may be centralized with a server for ranking the importance of read messages based on the relationships and addressing NL text messages to other social units or groups of social units based on the relationships. The platform further enables direct messaging between social unit devices, brokering trust, and moderating information flow between devices.Type: ApplicationFiled: November 9, 2017Publication date: April 4, 2019Inventors: Vincent Lonij, Bradley Eck, Amadou Ba
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Publication number: 20190065988Abstract: Techniques that facilitate semantic and time series analysis using machine learning are provided. In one example, a system includes a data analysis component, a prediction component and a learning component. The data analysis component that establishes one or more relationships between one or more elements of semantic data, including one or more time series identifiers, and one or more elements of time series data in a relationship database. The prediction component generates one or more advisory outputs, wherein generation of the one or more advisory outputs is performed in response to a trigger event, a learning component that determines the one or more relationships in the relationship database, wherein determination of the one or more relationships is based on information indicative of whether the advisory outputs satisfy a defined criterion.Type: ApplicationFiled: August 30, 2017Publication date: February 28, 2019Inventors: Bradley Eck, Vincent Lonij, Pascal Pompey
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Publication number: 20190065992Abstract: Techniques that facilitate semantic and time series analysis using machine learning are provided. In one example, a system includes a data analysis component, a prediction component and a learning component. The data analysis component that establishes one or more relationships between one or more elements of semantic data, including one or more time series identifiers, and one or more elements of time series data in a relationship database. The prediction component generates one or more advisory outputs, wherein generation of the one or more advisory outputs is performed in response to a trigger event. A learning component that determines the one or more relationships in the relationship database, wherein determination of the one or more relationships is based on information indicative of whether the advisory outputs satisfy a defined criterion.Type: ApplicationFiled: December 14, 2017Publication date: February 28, 2019Inventors: Bradley Eck, Vincent Lonij, Pascal Pompey
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Patent number: 10061279Abstract: An apparatus, method and computer program product for scheduling on/off control of equipment. The method implements an iterative approach that uses one objective and sets a tolerance value on the other objectives. Initially, the method computes the value of the different objective functions given a current feasible solution. The different objective functions are iteratively evaluated with respect to the current solution and a margin is set for every objective at each iteration. The margin is a deviation measure indicating the acceptable range by which each objective can be worsened. The method iteratively optimizes each objective function with respect to one of the objectives, following an order, while enforcing a maximum deviation on the other objective functions by setting them as constraints. The allowable deviation margin is then decreased for all the objective functions. A final output schedule is provided from which signals may be generated to automatically turn on/off the equipment.Type: GrantFiled: September 29, 2015Date of Patent: August 28, 2018Assignee: International Business Machines CorporationInventors: Bradley Eck, Bissan Ghaddar, Akihiro Kishimoto, Joe Naoum-Sawaya
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Publication number: 20170090440Abstract: An apparatus, method and computer program product for scheduling on/off control of equipment. The method implements an iterative approach that uses one objective and sets a tolerance value on the other objectives. Initially, the method computes the value of the different objective functions given a current feasible solution. The different objective functions are iteratively evaluated with respect to the current solution and a margin is set for every objective at each iteration. The margin is a deviation measure indicating the acceptable range by which each objective can be worsened. The method iteratively optimizes each objective function with respect to one of the objectives, following an order, while enforcing a maximum deviation on the other objective functions by setting them as constraints. The allowable deviation margin is then decreased for all the objective functions. A final output schedule is provided from which signals may be generated to automatically turn on/off the equipment.Type: ApplicationFiled: September 29, 2015Publication date: March 30, 2017Inventors: Bradley Eck, Bissan Ghaddar, Akihiro Kishimoto, Joe Naoum-Sawaya
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Patent number: 9255827Abstract: A method for estimating a fluid flow velocity may include receiving, with a processing device, a plurality of observations corresponding to a concentration of a constituent of a flowing fluid mixture, and computing a final estimate of an average velocity of the flowing fluid mixture based at least in part on the observations, wherein the constituent is undergoing a chemical reaction and the computing implements a reactive transport model.Type: GrantFiled: December 26, 2013Date of Patent: February 9, 2016Assignee: International Business Machines CorporationInventors: Bradley Eck, Sergiy Zhuk