Patents by Inventor Daniel ERENRICH
Daniel ERENRICH 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: 11907175Abstract: A model management system provides a centralized repository for storing and accessing models. The model management system receives an input to store a model object in a first model state generated based on a first set of known variables. The model management system generates a first file including a first set of functions defining the first model state and associates the first file with a model key identifying the model object. The model management system receives an input to store the model object in a second model state having been generated based on the first model state and a second set of known variables. The model management system generates a second file including a second set of functions defining the second model state and associates the second file with the model key. The model management system identifies available versions of the model object based on the model key.Type: GrantFiled: October 31, 2022Date of Patent: February 20, 2024Assignee: Palantir Technologies Inc.Inventors: David Lisuk, Daniel Erenrich, Guodong Xu, Luis Voloch, Rahul Agarwal, Simon Slowik, Aleksandr Zamoshchin, Andre Frederico Cavalheiro Menck, Anirvan Mukherjee, Daniel Chin
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Patent number: 11861515Abstract: Systems and methods are disclosed for determining a propensity of an entity to take a specified action. In accordance with one implementation, a method is provided for determining the propensity. The method includes, for example, accessing one or more data sources, the one or more data sources including information associated with the entity, forming a record associated with the entity by integrating the information from the one or more data sources, generating, based on the record, one or more features associated with the entity, processing the one or more features to determine the propensity of the entity to take the specified action, and outputting the propensity.Type: GrantFiled: October 7, 2022Date of Patent: January 2, 2024Assignee: Palantir Technologies Inc.Inventors: Daniel Erenrich, Anirvan Mukherjee
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Publication number: 20230297582Abstract: Computer implemented systems and methods are disclosed for automatically clustering and canonically identifying related data in various data structures. Data structures may include a plurality of records, wherein each record is associated with a respective entity. In accordance with some embodiments, the systems and methods further comprise identifying clusters of records associated with a respective entity by grouping the records into pairs, analyzing the respective pairs to determine a probability that both members of the pair relate to a common entity, and identifying a cluster of overlapping pairs to generate a collection of records relating to a common entity. Clusters may further be analyzed to determine canonical names or other properties for the respective entities by analyzing record fields and identifying similarities.Type: ApplicationFiled: May 30, 2023Publication date: September 21, 2023Inventors: Lawrence Manning, Rahul Mehta, Daniel Erenrich, Guillem Palou Visa, Roger Hu, Xavier Falco, Rowan Gilmore, Eli Bingham, Jason Prestinario, Yifei Huang, Daniel Fernandez, Jeremy Elser, Clayton Sader, Rahul Agarwal, Matthew Elkherj, Nicholas Latourette, Aleksandr Zamoshchin
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Patent number: 11704325Abstract: Computer implemented systems and methods are disclosed for automatically clustering and canonically identifying related data in various data structures. Data structures may include a plurality of records, wherein each record is associated with a respective entity. In accordance with some embodiments, the systems and methods further comprise identifying clusters of records associated with a respective entity by grouping the records into pairs, analyzing the respective pairs to determine a probability that both members of the pair relate to a common entity, and identifying a cluster of overlapping pairs to generate a collection of records relating to a common entity. Clusters may further be analyzed to determine canonical names or other properties for the respective entities by analyzing record fields and identifying similarities.Type: GrantFiled: July 15, 2022Date of Patent: July 18, 2023Assignee: Palantir Technologies Inc.Inventors: Lawrence Manning, Rahul Mehta, Daniel Erenrich, Guillem Palou Visa, Roger Hu, Xavier Falco, Rowan Gilmore, Eli Bingham, Jason Prestinario, Yifei Huang, Daniel Fernandez, Jeremy Elser, Clayton Sader, Rahul Agarwal, Matthew Elkherj, Nicholas Latourette, Aleksandr Zamoshchin
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Publication number: 20230081135Abstract: A model management system provides a centralized repository for storing and accessing models. The model management system receives an input to store a model object in a first model state generated based on a first set of known variables. The model management system generates a first file including a first set of functions defining the first model state and associates the first file with a model key identifying the model object. The model management system receives an input to store the model object in a second model state having been generated based on the first model state and a second set of known variables. The model management system generates a second file including a second set of functions defining the second model state and associates the second file with the model key. The model management system identifies available versions of the model object based on the model key.Type: ApplicationFiled: October 31, 2022Publication date: March 16, 2023Inventors: David Lisuk, Daniel Erenrich, Guodong Xu, Luis Voloch, Rahul Agarwal, Simon Slowik, Aleksandr Zamoshichin, Andre Frederico Cavalheiro Menck, Anirvan Mukherjee, Daniel Chin
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Publication number: 20230034067Abstract: Systems and methods are disclosed for determining a propensity of an entity to take a specified action. In accordance with one implementation, a method is provided for determining the propensity. The method includes, for example, accessing one or more data sources, the one or more data sources including information associated with the entity, forming a record associated with the entity by integrating the information from the one or more data sources, generating, based on the record, one or more features associated with the entity, processing the one or more features to determine the propensity of the entity to take the specified action, and outputting the propensity.Type: ApplicationFiled: October 7, 2022Publication date: February 2, 2023Inventors: Daniel Erenrich, Anirvan Mukherjee
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Publication number: 20230008175Abstract: Systems and methods are provided for selecting training examples to increase the efficiency of supervised active machine learning processes. Training examples for presentation to a user may be selected according to measure of the model's uncertainty in labeling the examples. A number of training examples may be selected to increase efficiency between the user and the processing system by selecting the number of training examples to minimize user downtime in the machine learning process.Type: ApplicationFiled: September 6, 2022Publication date: January 12, 2023Inventors: Daniel Erenrich, Matthew Elkherj
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Patent number: 11526471Abstract: A model management system provides a centralized repository for storing and accessing models. The model management system receives an input to store a model object in a first model state generated based on a first set of known variables. The model management system generates a first file including a first set of functions defining the first model state and associates the first file with a model key identifying the model object. The model management system receives an input to store the model object in a second model state having been generated based on the first model state and a second set of known variables. The model management system generates a second file including a second set of functions defining the second model state and associates the second file with the model key. The model management system identifies available versions of the model object based on the model key.Type: GrantFiled: November 9, 2020Date of Patent: December 13, 2022Assignee: Palantir Technologies Inc.Inventors: David Lisuk, Daniel Erenrich, Guodong Xu, Luis Voloch, Rahul Agarwal, Simon Slowik, Aleksandr Zamoshchin, Andre Frederico Cavalheiro Menck, Anirvan Mukherjee, Daniel Chin
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Patent number: 11521096Abstract: Systems and methods are disclosed for determining a propensity of an entity to take a specified action. In accordance with one implementation, a method is provided for determining the propensity. The method includes, for example, accessing one or more data sources, the one or more data sources including information associated with the entity, forming a record associated with the entity by integrating the information from the one or more data sources, generating, based on the record, one or more features associated with the entity, processing the one or more features to determine the propensity of the entity to take the specified action, and outputting the propensity.Type: GrantFiled: August 29, 2017Date of Patent: December 6, 2022Assignee: Palantir Technologies Inc.Inventors: Daniel Erenrich, Anirvan Mukherjee
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Publication number: 20220374454Abstract: Computer implemented systems and methods are disclosed for automatically clustering and canonically identifying related data in various data structures. Data structures may include a plurality of records, wherein each record is associated with a respective entity. In accordance with some embodiments, the systems and methods further comprise identifying clusters of records associated with a respective entity by grouping the records into pairs, analyzing the respective pairs to determine a probability that both members of the pair relate to a common entity, and identifying a cluster of overlapping pairs to generate a collection of records relating to a common entity. Clusters may further be analyzed to determine canonical names or other properties for the respective entities by analyzing record fields and identifying similarities.Type: ApplicationFiled: July 15, 2022Publication date: November 24, 2022Inventors: Lawrence Manning, Rahul Mehta, Daniel Erenrich, Guillem Palou Visa, Roger Hu, Xavier Falco, Rowan Gilmore, Eli Bingham, Jason Prestinario, Yifei Huang, Daniel Fernandez, Jeremy Elser, Clayton Sader, Rahul Agarwal, Matthew Elkherj, Nicholas Latourette, Aleksandr Zamoshchin
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Patent number: 11488058Abstract: In various example embodiments, a vector modeling system is configured to access a set of data distributed across client devices and stored in a structured format. The vector modeling system determines vector parameters and vector templates suitable for the set of data and transforms the set of data from the structured format into a second format including one or more vectors based on one or more transformation strategies. The vector modeling system stores the transformed data and performs machine learning analysis on the vector.Type: GrantFiled: May 30, 2019Date of Patent: November 1, 2022Assignee: Palantir Technologies Inc.Inventors: Rahul Agarwal, Daniel Erenrich
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Patent number: 11436523Abstract: Systems and methods are provided for selecting training examples to increase the efficiency of supervised active machine learning processes. Training examples for presentation to a user may be selected according to measure of the model's uncertainty in labeling the examples. A number of training examples may be selected to increase efficiency between the user and the processing system by selecting the number of training examples to minimize user downtime in the machine learning process.Type: GrantFiled: July 3, 2018Date of Patent: September 6, 2022Assignee: Palantir Technologies Inc.Inventors: Daniel Erenrich, Matthew Elkherj
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Patent number: 11392591Abstract: Computer implemented systems and methods are disclosed for automatically clustering and canonically identifying related data in various data structures. Data structures may include a plurality of records, wherein each record is associated with a respective entity. In accordance with some embodiments, the systems and methods further comprise identifying clusters of records associated with a respective entity by grouping the records into pairs, analyzing the respective pairs to determine a probability that both members of the pair relate to a common entity, and identifying a cluster of overlapping pairs to generate a collection of records relating to a common entity. Clusters may further be analyzed to determine canonical names or other properties for the respective entities by analyzing record fields and identifying similarities.Type: GrantFiled: November 13, 2018Date of Patent: July 19, 2022Assignee: Palantir Technologies Inc.Inventors: Lawrence Manning, Rahul Mehta, Daniel Erenrich, Guillem Palou Visa, Roger Hu, Xavier Falco, Rowan Gilmore, Eli Bingham, Jason Prestinario, Yifei Huang, Daniel Fernandez, Jeremy Elser, Clayton Sader, Rahul Agarwal, Matthew Elkherj, Nicholas Latourette, Aleksandr Zamoshchin
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Patent number: 10956431Abstract: Computer implemented systems and methods are disclosed for associating records across lists, wherein the lists include a plurality of records and the plurality of records is associated with a respective entity. In accordance with some embodiments, the systems and methods further comprise grouping one or more records from a first list into a first group based on fields of the records in the first list, grouping one or more records from a second list into a second group based on fields of the records in the second list, pairing a record from the first group with a record from the second group, assessing each pair of records based on an evaluation of the respective pair according to fields of the pair, and associating records from the first group and records of the second group with an entity based on the assessment.Type: GrantFiled: February 21, 2019Date of Patent: March 23, 2021Assignee: Palantir Technologies Inc.Inventors: Daniel Erenrich, Christian Tessier-Lavigne
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Publication number: 20210056083Abstract: A model management system provides a centralized repository for storing and accessing models. The model management system receives an input to store a model object in a first model state generated based on a first set of known variables. The model management system generates a first file including a first set of functions defining the first model state and associates the first file with a model key identifying the model object. The model management system receives an input to store the model object in a second model state having been generated based on the first model state and a second set of known variables. The model management system generates a second file including a second set of functions defining the second model state and associates the second file with the model key. The model management system identifies available versions of the model object based on the model key.Type: ApplicationFiled: November 9, 2020Publication date: February 25, 2021Inventors: David Lisuk, Daniel Erenrich, Guodong Xu, Luis Voloch, Rahul Agarwal, Simon Slowik, Aleksandr Zamoshchin, Andre Frederico Cavalheiro Menck, Anirvan Mukherjee, Daniel Chin
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Patent number: 10866936Abstract: A model management system provides a centralized repository for storing and accessing models. The model management system receives an input to store a model object in a first model state generated based on a first set of known variables. The model management system generates a first file including a first set of functions defining the first model state and associates the first file with a model key identifying the model object. The model management system receives an input to store the model object in a second model state having been generated based on the first model state and a second set of known variables. The model management system generates a second file including a second set of functions defining the second model state and associates the second file with the model key. The model management system identifies available versions of the model object based on the model key.Type: GrantFiled: February 8, 2018Date of Patent: December 15, 2020Assignee: Palantir Technologies Inc.Inventors: David Lisuk, Daniel Erenrich, Guodong Xu, Luis Voloch, Rahul Agarwal, Simon Slowik, Aleksandr Zamoshchin, Andre Frederico Cavalheiro Menck, Anirvan Mukherjee, Daniel Chin
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Publication number: 20200005181Abstract: In various example embodiments, a vector modeling system is configured to access a set of data distributed across client devices and stored in a structured format. The vector modeling system determines vector parameters and vector templates suitable for the set of data and transforms the set of data from the structured format into a second format including one or more vectors based on one or more transformation strategies. The vector modeling system stores the transformed data and performs machine learning analysis on the vector.Type: ApplicationFiled: May 30, 2019Publication date: January 2, 2020Inventors: Rahul Agarwal, Daniel Erenrich
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Patent number: 10373078Abstract: In various example embodiments, a vector modeling system is configured to access a set of data distributed across client devices and stored in a structured format. The vector modeling system determines vector parameters and vector templates suitable for the set of data and transforms the set of data from the structured format into a second format including one or more vectors based on one or more transformation strategies. The vector modeling system stores the transformed data and performs machine learning analysis on the vector.Type: GrantFiled: July 20, 2017Date of Patent: August 6, 2019Assignee: Palantir Technologies Inc.Inventors: Rahul Agarwal, Daniel Erenrich
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Publication number: 20190188200Abstract: Computer implemented systems and methods are disclosed for associating records across lists, wherein the lists include a plurality of records and the plurality of records is associated with a respective entity. In accordance with some embodiments, the systems and methods further comprise grouping one or more records from a first list into a first group based on fields of the records in the first list, grouping one or more records from a second list into a second group based on fields of the records in the second list, pairing a record from the first group with a record from the second group, assessing each pair of records based on an evaluation of the respective pair according to fields of the pair, and associating records from the first group and records of the second group with an entity based on the assessment.Type: ApplicationFiled: February 21, 2019Publication date: June 20, 2019Inventors: Daniel Erenrich, Christian Tessier-Lavigne
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Patent number: 10325224Abstract: Systems and methods are provided for selecting training examples to increase the efficiency of supervised active machine learning processes. Training examples for presentation to a user may be selected according to measure of the model's uncertainty in labeling the examples. A number of training examples may be selected to increase efficiency between the user and the processing system by selecting the number of training examples to minimize user downtime in the machine learning process.Type: GrantFiled: July 7, 2017Date of Patent: June 18, 2019Assignee: Palantir Technologies Inc.Inventors: Daniel Erenrich, Matthew Elkherj