Patents by Inventor Sergey SLEPIAN
Sergey SLEPIAN 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: 11960575Abstract: Embodiments of the present invention are directed to facilitating data preprocessing for machine learning. In accordance with aspects of the present disclosure, a training set of data is accessed. A preprocessing query specifying a set of preprocessing parameter values that indicate a manner in which to preprocess the training set of data is received. Based on the preprocessing query, a preprocessing operation is performed to preprocess the training set of data in accordance with the set of preprocessing parameter values to obtain a set of preprocessed data. The set of preprocessed data can be provided for presentation as a preview. Based on an acceptance of the set of preprocessed data, the set of preprocessed data is used to train a machine learning model that can be subsequently used to predict data.Type: GrantFiled: October 27, 2022Date of Patent: April 16, 2024Assignee: Splunk Inc.Inventors: Manish Sainani, Sergey Slepian, Di Lu, Adam Oliner, Jacob Leverich, Iryna Vogler-Ivashchanka, Iman Makaremi
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Patent number: 11574242Abstract: Techniques are described for providing a ML data analytics application including guided ML workflows that facilitate the end-to-end training and use of various types of ML models, where such guided workflows may also be referred to as ML “experiments.” For example, the ML data analytics application may enable users to create experiments related to prediction of numeric fields (for example, using linear regression techniques), predicting categorical fields (for example, using logistic regression), detecting numerical outliers (for example, using various distribution statistics), detecting categorical outliers (for example, using probabilistic statistics), forecasting time series data, and clustering numeric events (for example, using k-means, density-based spatial clustering of applications with noise (DBSCAN), spectral clustering, or other techniques), among other possible uses of various types of ML models to analyze data.Type: GrantFiled: April 30, 2019Date of Patent: February 7, 2023Assignee: Splunk Inc.Inventors: Cory Eugene Burke, Gyanendra Rana, Sergey Slepian, Andrew Stein, Iryna Vogler-Ivashchanka
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Patent number: 11514278Abstract: Embodiments of the present invention are directed to facilitating data preprocessing for machine learning. In accordance with aspects of the present disclosure, a training set of data is accessed. A preprocessing query specifying a set of preprocessing parameter values that indicate a manner in which to preprocess the training set of data is received. Based on the preprocessing query, a preprocessing operation is performed to preprocess the training set of data in accordance with the set of preprocessing parameter values to obtain a set of preprocessed data. The set of preprocessed data can be provided for presentation as a preview. Based on an acceptance of the set of preprocessed data, the set of preprocessed data is used to train a machine learning model that can be subsequently used to predict data.Type: GrantFiled: September 23, 2020Date of Patent: November 29, 2022Assignee: SPLUNK Inc.Inventors: Manish Sainani, Sergey Slepian, Di Lu, Adam Oliner, Jacob Leverich, Iryna Vogler-Ivashchanka, Iman Makaremi
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Patent number: 11194794Abstract: Embodiments of the present invention are directed to facilitating search input recommendations. In accordance with aspects of the present disclosure, a set of events determined from raw machine data is obtained. The events are analyzed to generate a temporal map associated with the set of events. Generally, the temporal map associates candidate terms with temporally related terms that occur within a period of time corresponding with the candidate terms. A search term input into a search field is received. Based on the input search term, the temporal map is used to identify one or more temporally related term recommendations.Type: GrantFiled: January 31, 2017Date of Patent: December 7, 2021Assignee: Splunk Inc.Inventors: Adam Jamison Oliner, Hongyang Zhang, Sergey Slepian, Di Lu, XiaoYu Jia, Peter Chongjin Kim, Manish Sainani
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Publication number: 20210192395Abstract: Disclosed herein is a computer-implemented tool that facilitates data analysis by use of machine learning (ML) techniques. The tool cooperates with a data intake and query system and provides a graphical user interface (GUI) that enables a user to train and apply a variety of different ML models on user-selected datasets of stored machine data. The tool can provide active guidance to the user, to help the user choose data analysis paths that are likely to produce useful results and to avoid data analysis paths that are less likely to produce useful results.Type: ApplicationFiled: March 3, 2021Publication date: June 24, 2021Inventors: Manish Sainani, Sergey Slepian, Iman Makaremi, Adam Jamison Oliner, Jacob Leverich, Di Lu
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Patent number: 10956834Abstract: Disclosed herein is a computer-implemented tool that facilitates data analysis by use of machine learning (ML) techniques. The tool cooperates with a data intake and query system and provides a graphical user interface (GUI) that enables a user to train and apply a variety of different ML models on user-selected datasets of stored machine data. The tool can provide active guidance to the user, to help the user choose data analysis paths that are likely to produce useful results and to avoid data analysis paths that are less likely to produce useful results.Type: GrantFiled: December 9, 2019Date of Patent: March 23, 2021Assignee: SPLUNK INC.Inventors: Manish Sainani, Sergey Slepian, Iman Makaremi, Adam Jamison Oliner, Jacob Leverich, Di Lu
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Publication number: 20210004651Abstract: Embodiments of the present invention are directed to facilitating data preprocessing for machine learning. In accordance with aspects of the present disclosure, a training set of data is accessed. A preprocessing query specifying a set of preprocessing parameter values that indicate a manner in which to preprocess the training set of data is received. Based on the preprocessing query, a preprocessing operation is performed to preprocess the training set of data in accordance with the set of preprocessing parameter values to obtain a set of preprocessed data. The set of preprocessed data can be provided for presentation as a preview. Based on an acceptance of the set of preprocessed data, the set of preprocessed data is used to train a machine learning model that can be subsequently used to predict data.Type: ApplicationFiled: September 23, 2020Publication date: January 7, 2021Inventors: Manish Sainani, Sergey Slepian, Di Lu, Adam Oliner, Jacob Leverich, Iryna Vogler-Ivashchanka, Iman Makaremi
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Patent number: 10817757Abstract: Embodiments of the present invention are directed to facilitating data preprocessing for machine learning. In accordance with aspects of the present disclosure, a training set of data is accessed. A preprocessing query specifying a set of preprocessing parameter values that indicate a manner in which to preprocess the training set of data is received. Based on the preprocessing query, a preprocessing operation is performed to preprocess the training set of data in accordance with the set of preprocessing parameter values to obtain a set of preprocessed data. The set of preprocessed data can be provided for presentation as a preview. Based on an acceptance of the set of preprocessed data, the set of preprocessed data is used to train a machine learning model that can be subsequently used to predict data.Type: GrantFiled: July 31, 2017Date of Patent: October 27, 2020Assignee: SPLUNK INC.Inventors: Manish Sainani, Sergey Slepian, Di Lu, Adam Oliner, Jacob Leverich, Iryna Vogler-Ivashchanka, Iman Makaremi
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Publication number: 20200118030Abstract: Disclosed herein is a computer-implemented tool that facilitates data analysis by use of machine learning (ML) techniques. The tool cooperates with a data intake and query system and provides a graphical user interface (GUI) that enables a user to train and apply a variety of different ML models on user-selected datasets of stored machine data. The tool can provide active guidance to the user, to help the user choose data analysis paths that are likely to produce useful results and to avoid data analysis paths that are less likely to produce useful results.Type: ApplicationFiled: December 9, 2019Publication date: April 16, 2020Inventors: Manish SAINANI, Sergey SLEPIAN, Iman MAKAREMI, Adam Jamison OLINER, Jacob LEVERICH, Di LU
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Patent number: 10607150Abstract: Disclosed herein is a computer-implemented tool that facilitates data analysis by use of machine learning (ML) techniques. The tool cooperates with a data intake and query system and provides a graphical user interface (GUI) that enables a user to train and apply a variety of different ML models on user-selected datasets of stored machine data. The tool can provide active guidance to the user, to help the user choose data analysis paths that are likely to produce useful results and to avoid data analysis paths that are less likely to produce useful results.Type: GrantFiled: February 23, 2016Date of Patent: March 31, 2020Assignee: SPLUNK INC.Inventors: Manish Sainani, Sergey Slepian, Iman Makaremi, Adam Jamison Oliner, Jacob Leverich, Di Lu
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Publication number: 20190034767Abstract: Embodiments of the present invention are directed to facilitating data preprocessing for machine learning. In accordance with aspects of the present disclosure, a training set of data is accessed. A preprocessing query specifying a set of preprocessing parameter values that indicate a manner in which to preprocess the training set of data is received. Based on the preprocessing query, a preprocessing operation is performed to preprocess the training set of data in accordance with the set of preprocessing parameter values to obtain a set of preprocessed data. The set of preprocessed data can be provided for presentation as a preview. Based on an acceptance of the set of preprocessed data, the set of preprocessed data is used to train a machine learning model that can be subsequently used to predict data.Type: ApplicationFiled: July 31, 2017Publication date: January 31, 2019Inventors: Manish Sainani, Sergey Slepian, Di Lu, Adam Oliner, Jacob Leverich, Iryna Vogler-Ivashchanka, Iman Makaremi
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Publication number: 20180218285Abstract: Embodiments of the present invention are directed to facilitating search input recommendations. In accordance with aspects of the present disclosure, a set of events determined from raw machine data is obtained. The events are analyzed to generate a temporal map associated with the set of events. Generally, the temporal map associates candidate terms with temporally related terms that occur within a period of time corresponding with the candidate terms. A search term input into a search field is received. Based on the input search term, the temporal map is used to identify one or more temporally related term recommendations.Type: ApplicationFiled: January 31, 2017Publication date: August 2, 2018Inventors: Adam Jamison Oliner, Hongyang Zhang, Sergey Slepian, Di Lu, XiaoYu Jia, Peter Chongjin Kim, Manish Sainani
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Publication number: 20170243132Abstract: Disclosed herein is a computer-implemented tool that facilitates data analysis by use of machine learning (ML) techniques. The tool cooperates with a data intake and query system and provides a graphical user interface (GUI) that enables a user to train and apply a variety of different ML models on user-selected datasets of stored machine data. The tool can provide active guidance to the user, to help the user choose data analysis paths that are likely to produce useful results and to avoid data analysis paths that are less likely to produce useful results.Type: ApplicationFiled: February 23, 2016Publication date: August 24, 2017Inventors: Manish SAINANI, Sergey SLEPIAN, Iman MAKAREMI, Adam Jamison OLINER, Jacob LEVERICH, Di LU