Patents by Inventor Deepak Srinivas Turaga
Deepak Srinivas Turaga 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: 11295242Abstract: Split an input dataset into training and test datasets; the former includes a plurality of data examples, each represented as a feature vector, and having an associated true label. Split the training dataset into a plurality of training data subsets; for each, train a corresponding machine learning model to obtain a plurality of such models, and apply same to the test dataset to obtain a plurality of predicted labels and prediction scores. For each of the plurality of examples, compute an agreement metric based on a corresponding one of the associated true labels; corresponding ones of the predicted labels; and corresponding ones of the prediction scores. Based on the computed metric, select, for at least some of the true label values, appropriate ones of the data examples to be added to a regression set. Add the appropriate ones of the data examples from the test dataset to the regression set.Type: GrantFiled: November 13, 2019Date of Patent: April 5, 2022Assignee: International Business Machines CorporationInventors: Yuan-Chi Chang, Deepak Srinivas Turaga, Long Vu, Venkata Nagaraju Pavuluri, Saket Sathe, Rodrigue Ngueyep Tzoumpe
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Publication number: 20210142222Abstract: Split an input dataset into training and test datasets; the former includes a plurality of data examples, each represented as a feature vector, and having an associated true label. Split the training dataset into a plurality of training data subsets; for each, train a corresponding machine learning model to obtain a plurality of such models, and apply same to the test dataset to obtain a plurality of predicted labels and prediction scores. For each of the plurality of examples, compute an agreement metric based on a corresponding one of the associated true labels; corresponding ones of the predicted labels; and corresponding ones of the prediction scores. Based on the computed metric, select, for at least some of the true label values, appropriate ones of the data examples to be added to a regression set. Add the appropriate ones of the data examples from the test dataset to the regression set.Type: ApplicationFiled: November 13, 2019Publication date: May 13, 2021Inventors: Yuan-Chi Chang, Deepak Srinivas Turaga, Long Vu, Venkata Nagaraju Pavuluri, Saket Sathe, Rodrigue Ngueyep Tzoumpe
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Patent number: 10803076Abstract: An encoding system for encoding an event time series, the system including an inter-arrival time computing device configured to transform inter-arrival times between a plurality of input events into discrete time symbols and map the input events and the discrete time symbols using a dictionary to output a time gram representing a temporal dimension between a sequences of events.Type: GrantFiled: May 31, 2018Date of Patent: October 13, 2020Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Nagui Halim, Srinivasan Parthasarathy, Venkata N. Pavuluri, Daby Mousse Sow, Deepak Srinivas Turaga
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Patent number: 10699199Abstract: Techniques for autonomously generating a domain model and/or an action model based on unstructured data are provided. In one example, a computer implemented method can comprise extracting, by a system operatively coupled to a processor, a plurality of actions from a non-numerical language. The plurality of actions can achieve a goal. The computer-implemented method can also comprise generating, by the system, a domain model based on the plurality of actions. Further, the computer-implemented method can comprise generating, by the system, an action model based on the domain model. In various embodiments, the action model can comprise an action transition for accomplishing the goal.Type: GrantFiled: January 31, 2017Date of Patent: June 30, 2020Assignee: INTERNATIONAL BUSINESS MACHINES CORPROATIONInventors: Lydia Manikonda, Anton Viktorovich Riabov, Shirin Sohrabi Araghi, Biplav Srivastava, Kartik Talamadupula, Deepak Srinivas Turaga
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Patent number: 10699200Abstract: Techniques for autonomously generating a domain model and/or an action model based on unstructured data are provided. In one example, a computer implemented method can comprise extracting, by a system operatively coupled to a processor, a plurality of actions from a non-numerical language. The plurality of actions can achieve a goal. The computer-implemented method can also comprise generating, by the system, a domain model based on the plurality of actions. Further, the computer-implemented method can comprise generating, by the system, an action model based on the domain model. In various embodiments, the action model can comprise an action transition for accomplishing the goal.Type: GrantFiled: December 13, 2017Date of Patent: June 30, 2020Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Lydia Manikonda, Anton Viktorovich Riabov, Shirin Sohrabi Araghi, Biplav Srivastava, Kartik Talamadupula, Deepak Srinivas Turaga
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Publication number: 20180285425Abstract: An encoding system for encoding an event time series, the system including an inter-arrival time computing device configured to transform inter-arrival times between a plurality of input events into discrete time symbols and map the input events and the discrete time symbols using a dictionary to output a time gram representing a temporal dimension between a sequences of events.Type: ApplicationFiled: May 31, 2018Publication date: October 4, 2018Inventors: Nagui HALIM, Srinivasan PARTHASARATHY, Venkata N. PAVULURI, Daby Mousse SOW, Deepak Srinivas TURAGA
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Patent number: 10049140Abstract: An encoding system for encoding an event time series, the system including an inter-arrival time computing device configured to compute an inter-arrival time between a plurality of input events and computes a sequence of events, a transformation device configured to transform the inter-arrival time between the plurality of input events into discrete time symbols, and a mapping device configured to map the input events and the discrete time symbols using a dictionary to output a time gram.Type: GrantFiled: August 28, 2015Date of Patent: August 14, 2018Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Nagui Halim, Srinivasan Parthasarathy, Venkata N. Pavuluri, Daby Mousse Sow, Deepak Srinivas Turaga
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Publication number: 20180218270Abstract: Techniques for autonomously generating a domain model and/or an action model based on unstructured data are provided. In one example, a computer implemented method can comprise extracting, by a system operatively coupled to a processor, a plurality of actions from a non-numerical language. The plurality of actions can achieve a goal. The computer-implemented method can also comprise generating, by the system, a domain model based on the plurality of actions. Further, the computer-implemented method can comprise generating, by the system, an action model based on the domain model. In various embodiments, the action model can comprise an action transition for accomplishing the goal.Type: ApplicationFiled: January 31, 2017Publication date: August 2, 2018Inventors: Lydia Manikonda, Anton Viktorovich Riabov, Shirin Sohrabi Araghi, Biplav Srivastava, Kartik Talamadupula, Deepak Srinivas Turaga
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Publication number: 20180218272Abstract: Techniques for autonomously generating a domain model and/or an action model based on unstructured data are provided. In one example, a computer implemented method can comprise extracting, by a system operatively coupled to a processor, a plurality of actions from a non-numerical language. The plurality of actions can achieve a goal. The computer-implemented method can also comprise generating, by the system, a domain model based on the plurality of actions. Further, the computer-implemented method can comprise generating, by the system, an action model based on the domain model. In various embodiments, the action model can comprise an action transition for accomplishing the goal.Type: ApplicationFiled: December 13, 2017Publication date: August 2, 2018Inventors: Lydia Manikonda, Anton Viktorovich Riabov, Shirin Sohrabi Araghi, Biplav Srivastava, Kartik Talamadupula, Deepak Srinivas Turaga
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Publication number: 20170060962Abstract: An encoding system for encoding an event time series, the system including an inter-arrival time computing device configured to compute an inter-arrival time between a plurality of input events and computes a sequence of events, a transformation device configured to transform the inter-arrival time between the plurality of input events into discrete time symbols, and a mapping device configured to map the input events and the discrete time symbols using a dictionary to output a time gram.Type: ApplicationFiled: August 28, 2015Publication date: March 2, 2017Inventors: Nagui HALIM, Srinivasan PARTHASARATHY, Venkata N. PAVULURI, Daby Mousse SOW, Deepak Srinivas TURAGA
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Patent number: 7973715Abstract: A system to determine a direction of arrival of each of a plurality of constituent signals of a superimposed wave includes a tripole radio antenna, a sampling unit, a frequency determining unit, an amplitude and phase determining unit, and a direction determining unit. The sampling unit is configured to periodically sample an output of the tripole radio antenna to generate at least two samples. The frequency determining unit is configured to determine frequencies for each dimension of the constituent signals by performing a unitary matrix pencil method on the at least two samples. The amplitude and phase determining unit is configured to determine x, y, z amplitudes and x, y, z phases for each constituent signal using the determined frequencies. The direction determining unit is configured to determine a direction of arrival for each of the constituent signals from the determined frequencies, amplitudes, and phases.Type: GrantFiled: April 17, 2009Date of Patent: July 5, 2011Assignee: International Business Machines CorporationInventors: Alain Biem, Lars Kristen Selberg Daldorff, Deepak Srinivas Turaga, Olivier Verscheure
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Publication number: 20100265138Abstract: A system to determine a direction of arrival of each of a plurality of constituent signals of a superimposed wave includes a tripole radio antenna, a sampling unit, a frequency determining unit, an amplitude and phase determining unit, and a direction determining unit. The sampling unit is configured to periodically sample an output of the tripole radio antenna to generate at least two samples. The frequency determining unit is configured to determine frequencies for each dimension of the constituent signals by performing a unitary matrix pencil method on the at least two samples. The amplitude and phase determining unit is configured to determine x, y, z amplitudes and x, y, z phases for each constituent signal using the determined frequencies. The direction determining unit is configured to determine a direction of arrival for each of the constituent signals from the determined frequencies, amplitudes, and phases.Type: ApplicationFiled: April 17, 2009Publication date: October 21, 2010Inventors: ALAIN BIEM, LARS KRISTEN SELBERG DALDORFF, DEEPAK SRINIVAS TURAGA, OLIVIER VERSCHEURE
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Publication number: 20070276933Abstract: A computer-implemented method for delivering a level of quality of service for a client requesting data in a connection arrangement including a server and a plurality of clients assigned one of a plurality of classes, wherein the determination of the level of quality of service includes estimating an arrival rate of potential future requests of at least one class of the plurality of classes, determining a capacity of the at least one data server, determining a current load of the server, reserving a capacity for at least the one class of the plurality of classes according to an estimated arrival rate, assigning the server to the client, and serving the data to the client from an assigned data server, wherein an amount of capacity is allotted to the client according to the level of the quality of service.Type: ApplicationFiled: May 25, 2006Publication date: November 29, 2007Inventors: Nathan Junsup Lee, Krishna C. Ratakonda, Deepak Srinivas Turaga