Patents by Inventor Sanjay Nair
Sanjay Nair 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: 11593334Abstract: An apparatus, method and computer program product for physical database design and tuning in relational database management systems. A relational database management system executes in a computer system, wherein the relational database management system manages a relational database comprised of one or more tables storing data. A Deep Reinforcement Learning based feedback loop process also executes in the computer system for recommending one or more tuning actions for the physical database design and tuning of the relational database management system, wherein the Deep Reinforcement Learning based feedback loop process uses a neural network framework to select the tuning actions based on one or more query workloads performed by the relational database management system.Type: GrantFiled: December 27, 2019Date of Patent: February 28, 2023Assignee: Teradata US, Inc.Inventors: Louis Martin Burger, Emiran Curtmola, Sanjay Nair, Frank Roderic Vandervort, Douglas P. Brown
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Patent number: 11570465Abstract: A compression system trains a compression model for an encoder and decoder. In one embodiment, the compression model includes a machine-learned in-loop flow predictor that generates a flow prediction from previously reconstructed frames. The machine-learned flow predictor is coupled to receive a set of previously reconstructed frames and output a flow prediction for a target frame that is an estimation of the flow for the target frame. In particular, since the flow prediction can be generated by the decoder using the set of previously reconstructed frames, the encoder may transmit a flow delta that indicates a difference between the flow prediction and the actual flow for the target frame, instead of transmitting the flow itself. In this manner, the encoder can transmit a significantly smaller number of bits to the receiver, improving computational efficiency.Type: GrantFiled: August 25, 2021Date of Patent: January 31, 2023Assignee: WaveOne Inc.Inventors: Oren Rippel, Alexander G. Anderson, Kedar Tatwawadi, Sanjay Nair, Craig Lytle, Hervé Guihot, Brandon Sprague, Lubomir Bourdev
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Publication number: 20230018461Abstract: A cloud service system manages a filter repository including filters for encoding and decoding media content (e.g. text, image, audio, video, etc.). The cloud service system may receive a request from a client device to provide a filter for installation on a node such as an endpoint device (e.g. pipeline node). The request includes information such as a type of bitstream to be processed by the requested filter. The request may further include other information such as hardware configuration and functionality attribute. The cloud service system may access the filter repository that stores the plurality of filters including encoder filters and decoder filters and may select a filter that is configured to process the type of bitstream identified in the request and provide the selected filter to the client device.Type: ApplicationFiled: July 13, 2021Publication date: January 19, 2023Inventors: Lubomir Bourdev, Alexander G. Anderson, Kedar Tatwawadi, Sanjay Nair, Craig Lytle, Hervé Guihot, Brandon Sprague, Oren Rippel
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Patent number: 11473803Abstract: A plurality of triggers may be presented and a selection of a predefined trigger may be accepted. Corresponding actions for the selected trigger may then be presented and an assignment of building control components may be accepted for the corresponding actions. During subsequent operation of a building automation system, the selected trigger may be detected and the corresponding actions may then be performed on the assigned building control components.Type: GrantFiled: July 5, 2017Date of Patent: October 18, 2022Assignee: HONEYWELL INTERNATIONAL INC.Inventors: Franklin Joseph, Nilesh Akode, Sanjay Nair, Venugopala Kilingar Nadumane, Manish K. Sharma, Sheeladitya Karmakar, Rajendra S. Kumar
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Publication number: 20220315589Abstract: The invention relates to substituted nucleoside analogues of formula (I), pharmaceutically acceptable salts thereof and pharmaceutical compositions for treating diseases, disorders or conditions associated with the overexpression of PRMT5 enzyme. The invention also relates to methods of treating diseases, disorders or conditions associated with the overexpression of PRMT5 enzyme.Type: ApplicationFiled: June 9, 2020Publication date: October 6, 2022Inventors: Prathap Sreedharan Nair, Ganesh Bhausaheb Gudade, Mahadeo Bhaskar Tryambake, Chetan Sanjay Pawar, Dipak Raychand Lagad, Chaitanya Prabhakar Kulkarni, Milind Dattatraya Sindkhedkar, Venkata P. Palle, Rajender Kumar Kamboj
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Patent number: 11459330Abstract: The invention relates to substituted bicyclic heterocyclic compounds of formula (I), pharmaceutically acceptable salts thereof and pharmaceutical compositions for treating diseases, disorders or conditions associated with the overexpression of PRMT5 enzyme. The invention also relates to methods of treating diseases, disorders or conditions associated with the overexpression of PRMT5 enzyme.Type: GrantFiled: December 13, 2018Date of Patent: October 4, 2022Assignee: LUPIN LIMITEDInventors: Prathap Sreedharan Nair, Ganesh Bhausaheb Gudade, Sachin Sethi, Dipak Raychand Lagad, Chetan Sanjay Pawar, Mahadeo Bhaskar Tryambake, Chaitanya Prabhakar Kulkarni, Anil Kashiram Hajare, Balasaheb Arjun Gore, Sanjeev Anant Kulkarni, Milind Dattatraya Sindkhedkar, Venkata P. Palle, Rajender Kumar Kamboj
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Publication number: 20220267339Abstract: The invention relates to substituted bicyclic heterocyclic compounds of formula (I), pharmaceutically acceptable salts thereof and pharmaceutical compositions for treating diseases, disorders or conditions associated with the overexpression of PRMT5 enzyme. The invention also relates to methods of treating diseases, disorders or conditions associated with the overexpression of PRMT5 enzyme.Type: ApplicationFiled: May 6, 2022Publication date: August 25, 2022Applicant: LUPIN LIMITEDInventors: Prathap Sreedharan Nair, Ganesh Bhausaheb Gudade, Sachin Sethi, Dipak Raychand Lagad, Chetan Sanjay Pawar, Mahadeo Bhaskar Tryambake, Chaitanya Prabhakar Kulkarni, Anil Kashiram Hajare, Balasaheb Arjun Gore, Sanjeev Anant Kulkarni, Milind Dattatraya Sindkhedkar, Venkata P. Palle, Rajender Kumar Kamboj
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Patent number: 11409743Abstract: In some examples, a system learns properties of an analytical function based on information of queries invoking the analytical function that have been previously executed, creates a function descriptor for the analytical function based on the learning, and provides the function descriptor for use by an optimizer in generating an execution plan for a received database query that includes the analytical function.Type: GrantFiled: December 23, 2019Date of Patent: August 9, 2022Assignee: Teradata US, Inc.Inventors: Mohamed Ahmed Yassin Eltabakh, Mohammed Al-Kateb, Awny Kayed Al-Omari, Sanjay Nair
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Publication number: 20220224934Abstract: A compression system trains a compression model for an encoder and decoder. In one embodiment, the compression model includes a machine-learned in-loop flow predictor that generates a flow prediction from previously reconstructed frames. The machine-learned flow predictor is coupled to receive a set of previously reconstructed frames and output a flow prediction for a target frame that is an estimation of the flow for the target frame. In particular, since the flow prediction can be generated by the decoder using the set of previously reconstructed frames, the encoder may transmit a flow delta that indicates a difference between the flow prediction and the actual flow for the target frame, instead of transmitting the flow itself. In this manner, the encoder can transmit a significantly smaller number of bits to the receiver, improving computational efficiency.Type: ApplicationFiled: August 25, 2021Publication date: July 14, 2022Inventors: Oren Rippel, Alexander G. Anderson, Kedar Tatwawadi, Sanjay Nair, Craig Lytle, Hervé Guihot, Brandon Sprague, Lubomir Bourdev
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Publication number: 20220224914Abstract: A compression system trains a machine-learned compression model that includes components for an encoder and decoder. In one embodiment, the compression model is trained to receive parameter information on how a target frame should be encoded with respect to one or more encoding parameters, and encodes the target frame according to the respective values of the encoding parameters for the target frame. In particular, the encoder of the compression model includes at least an encoding system configured to encode a target frame and generate compressed code that can be transmitted by, for example, a sender system to a receiver system. The decoder of the compression model includes a decoding system trained in conjunction with the encoding system. The decoding system is configured to receive the compressed code for the target frame and reconstruct the target frame for the receiver system.Type: ApplicationFiled: September 3, 2021Publication date: July 14, 2022Inventors: Alexander G. Anderson, Oren Rippel, Kedar Tatwawadi, Sanjay Nair, Craig Lytle, Hervé Guihot, Brandon Sprague, Lubomir Bourdev
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Publication number: 20220207052Abstract: A method and apparatus for optimizing a query in a relational database management system (RDBMS) when a predicate on a data column in the query has a correlation to a partitioning attribute of a partitioning column in data retrieved from a cloud-based store, wherein the optimizing uses the correlation between the data column in the query to the partitioning column in the data retrieved from the cloud-based store for data elimination when processing the query. The correlation is defined in a formula or lookup data structure that maps or range-maps from the data column to the partitioning column.Type: ApplicationFiled: December 30, 2020Publication date: June 30, 2022Applicant: Teradata US, Inc.Inventors: Mohamed Ahmed Yassin Eltabakh, Mohammed Al-Kateb, Sanjay Nair, Awny Kayed Al-Omari
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Patent number: 11315011Abstract: The compression system trains a machine-learned encoder and decoder through an autoencoder architecture. The encoder can be deployed by a sender system to encode content for transmission to a receiver system, and the decoder can be deployed by the receiver system to decode the encoded content and reconstruct the original content. The encoder is coupled to receive content and output a tensor as a compact representation of the content. The content may be, for example, images, videos, or text. The decoder is coupled to receive a tensor representing content and output a reconstructed version of the content. The compression system trains the autoencoder with a discriminator to reduce compression artifacts in the reconstructed content. The discriminator is coupled to receive one or more input content, and output a discrimination prediction that discriminates whether the input content is the original or reconstructed version of the content.Type: GrantFiled: December 15, 2017Date of Patent: April 26, 2022Assignee: WaveOne Inc.Inventors: Oren Rippel, Lubomir Bourdev, Carissa Lew, Sanjay Nair
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Patent number: 11308053Abstract: A system and method for loading data into column-partitioned database tables. The system and method incorporate a mechanism for buffering data extracted from the rows of a source table in column-oriented fashion within an in-buffer memory, enabling an efficient bulk-write of large arrays of values from the buffer into column-partitioned database tables. The system and method may also include optimizations for grouping columns according to data types and altering the order in which columns are inserted into the database tables.Type: GrantFiled: October 27, 2016Date of Patent: April 19, 2022Assignee: Teradata US, Inc.Inventors: Rui Zhang, Sanjay Nair, Paul Laurence Sinclair, Mamatha Govind Rao
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Patent number: 11256984Abstract: A machine learning (ML) task system trains a neural network model that learns a compressed representation of acquired data and performs a ML task using the compressed representation. The neural network model is trained to generate a compressed representation that balances the objectives of achieving a target codelength and achieving a high accuracy of the output of the performed ML task. During deployment, an encoder portion and a task portion of the neural network model are separately deployed. A first system acquires data, applies the encoder portion to generate a compressed representation, performs an encoding process to generate compressed codes, and transmits the compressed codes. A second system regenerates the compressed representation from the compressed codes and applies the task model to determine the output of a ML task.Type: GrantFiled: December 15, 2017Date of Patent: February 22, 2022Assignee: WaveOne Inc.Inventors: Lubomir Bourdev, Carissa Lew, Sanjay Nair, Oren Rippel
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Patent number: 11113283Abstract: A query having a Union All view is identified. A logical join between Union AH view/derived table and other tables is broken down into multiple physical joins. The physical joins are pushed to the branches. Cost-based processing statistics are obtained for the branches. An optimal plan for the joins is selected based on the statistics; representing an optimal query execution for the query. The optimal query execution plan is provided to a database engine for executing the optimal query execution plan against a data warehouse.Type: GrantFiled: December 18, 2017Date of Patent: September 7, 2021Assignee: Teradata US, Inc.Inventors: Mohammed Al-Kateb, Grace Kwan-On Au, Rama Krishna Korlapati, Lu Ma, Sanjay Nair
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Patent number: 11086870Abstract: A data store system includes an array of persistent storage devices configured to store a plurality of data store tables. The data store system includes a processor in communication with the storage device. The processor may receive a query comprising an aggregate function and identify structure of an argument of the aggregate function. The subset of data store tables may be associated with the argument. The processor may partially-execute the aggregate function on each data store table in the subset involved in the argument of the aggregate function to create partially-executed results for each data store table of the subset of data store tables. The processor may join the partially-executed results based on join conditions contained in the aggregate function. The processor may complete execution of the aggregate function on the partially-executed results to generate a final result of the aggregate function. A method and computer-readable medium are also disclosed.Type: GrantFiled: December 30, 2015Date of Patent: August 10, 2021Assignee: Teradata US, Inc.Inventors: Anantha B. Subramanian, Sanjay Nair, Yi Xia, Grace Kwan-On Au, Kuorong Chiang
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Publication number: 20210140668Abstract: A plurality of triggers may be presented and a selection of a predefined trigger may be accepted. Corresponding actions for the selected trigger may then be presented and an assignment of building control components may be accepted for the corresponding actions. During subsequent operation of a building automation system, the selected trigger may be detected and the corresponding actions may then be performed on the assigned building control components.Type: ApplicationFiled: July 5, 2017Publication date: May 13, 2021Inventors: Franklin Joseph, Nilesh Akode, Sanjay Nair, Venugopala Kilingar Nadumane, Manish K. Sharma, Sheeladitya Karmakar, Rajendra S. Kumar
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Patent number: 10997168Abstract: One or a soft correlation of a database can be adjusted (e.g., modified, replaced, overwritten) for use with respect to one or more record(s) of the database associated with the soft correlation, by considering at least one or more violations of the soft correlations in the one or more of records database records associated with the soft correlation. In addition, an adjusted soft correlation can be stored and used for optimizations of database queries pertaining to one or more records associated with the adjusted soft correlation. Typically, the adjusted soft correlation is adjusted by at least considering the violations of an original soft correlation in the one or more records relating to the database queries.Type: GrantFiled: December 13, 2018Date of Patent: May 4, 2021Assignee: Teradata US, Inc.Inventors: Mohamed Yassin Eltabakh, Grace Kwan-On Au, Sanjay Nair, Mohammed Al-Kateb, Paul Laurence Sinclair
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Publication number: 20210056106Abstract: An apparatus, method and computer program product for query optimization in a Relational Database Management System (RDBMS), wherein an optimizer accesses a query expression repository (QER), so that the optimizer learns from previous versions of the queries to improve current and subsequent versions of the queries. The QER stores planning and execution information for QEs from the previous versions of the queries, wherein the QEs comprise table relations, intermediate results and/or final results of operations in the previous versions of the queries. The optimizer searches the QER for QEs from the query execution plans, and uses information from the QEs stored in the QER when optimizing the current and subsequent versions of the queries. The optimizer may also reuses results from the QEs stored in the QER.Type: ApplicationFiled: December 27, 2019Publication date: February 25, 2021Applicant: Teradata US, Inc.Inventors: Grace Kwan-On Au, Nobul Reddy Goli, Vivek Kumar, Ming Zhang, Bin Cao, Sanjay Nair, Kanaka Durga Rajanala, Sanjib Mishra, Naveen Jaiswal, Lu Ma, Xiaorong Luo
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Publication number: 20210034624Abstract: In some examples, a system learns properties of an analytical function based on information of queries invoking the analytical function that have been previously executed, creates a function descriptor for the analytical function based on the learning, and provides the function descriptor for use by an optimizer in generating an execution plan for a received database query that includes the analytical function.Type: ApplicationFiled: December 23, 2019Publication date: February 4, 2021Inventors: Mohamed Ahmed Yassin Eltabakh, Mohammed Al-Kateb, Awny Kayed Al-Omari, Sanjay Nair