Patents by Inventor Justin Derrick BASILICO
Justin Derrick BASILICO 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: 11782821Abstract: The disclosed computer-implemented method may include accessing updated data structures that are to be included in a user interface functionality test, where the updated data structures contribute to a user interface. The method may also include accessing live or snapshotted data captured from services running in a production environment, initiating generation of a first user interface instance using the updated data structures and using the accessed live or snapshotted data, and initiating generation of a second user interface instance using a different version of the data structures and using the same accessed live or snapshotted data. The method further includes comparing the first user interface instance to the second user interface instance to identify differences and then determine which outcome-defining effects the updated data structures had on the user interface based on the identified differences between the user interfaces.Type: GrantFiled: June 29, 2022Date of Patent: October 10, 2023Assignee: Netflix, Inc.Inventors: David Gevorkyan, Mehmet Yilmaz, Ajinkya More, Justin Derrick Basilico, Prasanna Padmanabhan, Vivek Kaushal, Gaurav Agrawal, Richard Wellington
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Patent number: 11522938Abstract: A system for utilizing models derived from offline historical data in online applications is provided. The system includes a processor and a memory storing machine-readable instructions for determining a set of contexts of the usage data, and for each of the contexts within the set of contexts, collecting service data from services supporting the media service and storing that service data in a database. The system performing an offline testing process by fetching service data for a defined context from the database, generating a first set of feature vectors based on the fetched service data, and providing the first set to a machine-learning module. The system performs an online testing process by fetching active service data from the services supporting the media streaming service, generating a second set of feature vectors based on the fetched active service data, and providing the second set to the machine-learning module.Type: GrantFiled: February 11, 2021Date of Patent: December 6, 2022Assignee: Netflix, Inc.Inventors: Mohammad Hossein Taghavi, Prasanna Padmanabhan, Dong-Bang Tsai, Faisal Zakaria Siddiqi, Justin Derrick Basilico
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Publication number: 20220334951Abstract: The disclosed computer-implemented method may include accessing updated data structures that are to be included in a user interface functionality test, where the updated data structures contribute to a user interface. The method may also include accessing live or snapshotted data captured from services running in a production environment, initiating generation of a first user interface instance using the updated data structures and using the accessed live or snapshotted data, and initiating generation of a second user interface instance using a different version of the data structures and using the same accessed live or snapshotted data. The method further includes comparing the first user interface instance to the second user interface instance to identify differences and then determine which outcome-defining effects the updated data structures had on the user interface based on the identified differences between the user interfaces.Type: ApplicationFiled: June 29, 2022Publication date: October 20, 2022Inventors: David GEVORKYAN, Mehmet YILMAZ, Ajinkya MORE, Justin Derrick BASILICO, Prasanna PADMANABHAN, Vivek KAUSHAL, Gaurav AGRAWA, Richard WELLINGTON
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Patent number: 11409637Abstract: The disclosed computer-implemented method may include accessing updated data structures that are to be included in a user interface functionality test, where the updated data structures contribute to a user interface. The method may also include accessing live or snapshotted data captured from services running in a production environment, initiating generation of a first user interface instance using the updated data structures and using the accessed live or snapshotted data, and initiating generation of a second user interface instance using a different version of the data structures and using the same accessed live or snapshotted data. The method further includes comparing the first user interface instance to the second user interface instance to identify differences and then determine which outcome-defining effects the updated data structures had on the user interface based on the identified differences between the user interfaces.Type: GrantFiled: January 17, 2020Date of Patent: August 9, 2022Assignee: Netflix, Inc.Inventors: David Gevorkyan, Mehmet Yilmaz, Ajinkya More, Justin Derrick Basilico, Prasanna Padmanabhan, Vivek Kaushal, Gaurav Agrawal, Richard Wellington
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Publication number: 20220180186Abstract: Various embodiments set forth systems and techniques for training a personalized prediction model. The techniques include generating, based on interaction data associated with one or more users and a first weight associated with the interaction data, a first set of training data; generating, based on the personalized prediction model, a predicted enjoyment signal associated with playback of a digital content item; generating, based on the first set of training data and the predicted enjoyment signal, a second set of training data; and updating one or more parameters of a personalized ranking model based on the second set of training data.Type: ApplicationFiled: March 4, 2021Publication date: June 9, 2022Inventors: Justin Derrick BASILICO, Jiangwei PAN
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Publication number: 20210168184Abstract: A system for utilizing models derived from offline historical data in online applications is provided. The system includes a processor and a memory storing machine-readable instructions for determining a set of contexts of the usage data, and for each of the contexts within the set of contexts, collecting service data from services supporting the media service and storing that service data in a database. The system performing an offline testing process by fetching service data for a defined context from the database, generating a first set of feature vectors based on the fetched service data, and providing the first set to a machine-learning module. The system performs an online testing process by fetching active service data from the services supporting the media streaming service, generating a second set of feature vectors based on the fetched active service data, and providing the second set to the machine-learning module.Type: ApplicationFiled: February 11, 2021Publication date: June 3, 2021Inventors: Mohammad Hossein Taghavi, Prasanna Padmanabhan, Dong-Bang Tsai, Faisal Zakaria Siddiqi, Justin Derrick Basilico
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Publication number: 20210141712Abstract: The disclosed computer-implemented method may include accessing updated data structures that are to be included in a user interface functionality test, where the updated data structures contribute to a user interface. The method may also include accessing live or snapshotted data captured from services running in a production environment, initiating generation of a first user interface instance using the updated data structures and using the accessed live or snapshotted data, and initiating generation of a second user interface instance using a different version of the data structures and using the same accessed live or snapshotted data. The method further includes comparing the first user interface instance to the second user interface instance to identify differences and then determine which outcome-defining effects the updated data structures had on the user interface based on the identified differences between the user interfaces.Type: ApplicationFiled: January 17, 2020Publication date: May 13, 2021Inventors: David Gevorkyan, Mehmet Yilmaz, Ajinkya More, Justin Derrick Basilico, Prasanna Padmanabhan, Vivek Kaushal, Gaurav Agrawa, Richard Wellington
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Patent number: 10958704Abstract: A system for utilizing models derived from offline historical data in online applications is provided. The system includes a processor and a memory storing machine-readable instructions for determining a set of contexts of the usage data, and for each of the contexts within the set of contexts, collecting service data from services supporting the media service and storing that service data in a database. The system performing an offline testing process by fetching service data for a defined context from the database, generating a first set of feature vectors based on the fetched service data, and providing the first set to a machine-learning module. The system performs an online testing process by fetching active service data from the services supporting the media streaming service, generating a second set of feature vectors based on the fetched active service data, and providing the second set to the machine-learning module.Type: GrantFiled: August 30, 2019Date of Patent: March 23, 2021Assignee: Netflix, Inc.Inventors: Mohammad Hossein Taghavi, Prasanna Padmanabhan, Dong-Bang Tsai, Faisal Zakaria Siddiqi, Justin Derrick Basilico
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Publication number: 20190394252Abstract: A system for utilizing models derived from offline historical data in online applications is provided. The system includes a processor and a memory storing machine-readable instructions for determining a set of contexts of the usage data, and for each of the contexts within the set of contexts, collecting service data from services supporting the media service and storing that service data in a database. The system performing an offline testing process by fetching service data for a defined context from the database, generating a first set of feature vectors based on the fetched service data, and providing the first set to a machine-learning module. The system performs an online testing process by fetching active service data from the services supporting the media streaming service, generating a second set of feature vectors based on the fetched active service data, and providing the second set to the machine-learning module.Type: ApplicationFiled: August 30, 2019Publication date: December 26, 2019Inventors: Mohammad Hossein Taghavi, Prasanna Padmanabhan, Dong-Bang Tsai, Faisal Zakaria Siddiqi, Justin Derrick Basilico
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Patent number: 10432689Abstract: A system for utilizing models derived from offline historical data in online applications is provided. The system includes a processor and a memory storing machine-readable instructions for determining a set of contexts of the usage data, and for each of the contexts within the set of contexts, collecting service data from services supporting the media service and storing that service data in a database. The system performing an offline testing process by fetching service data for a defined context from the database, generating a first set of feature vectors based on the fetched service data, and providing the first set to a machine-learning module. The system performs an online testing process by fetching active service data from the services supporting the media streaming service, generating a second set of feature vectors based on the fetched active service data, and providing the second set to the machine-learning module.Type: GrantFiled: October 21, 2016Date of Patent: October 1, 2019Assignee: Netflix, Inc.Inventors: Mohammad Hossein Taghavi, Prasanna Padmanabhan, Dong-Bang Tsai, Faisal Zakaria Siddiqi, Justin Derrick Basilico
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Publication number: 20170237792Abstract: A system for utilizing models derived from offline historical data in online applications is provided. The system includes a processor and a memory storing machine-readable instructions for determining a set of contexts of the usage data, and for each of the contexts within the set of contexts, collecting service data from services supporting the media service and storing that service data in a database. The system performing an offline testing process by fetching service data for a defined context from the database, generating a first set of feature vectors based on the fetched service data, and providing the first set to a machine-learning module. The system performs an online testing process by fetching active service data from the services supporting the media streaming service, generating a second set of feature vectors based on the fetched active service data, and providing the second set to the machine-learning module.Type: ApplicationFiled: October 21, 2016Publication date: August 17, 2017Inventors: Mohammad Hossein TAGHAVI, Prasanna PADMANABHAN, Dong-Bang TSAI, Faisal Zakaria SIDDIQI, Justin Derrick BASILICO