User behavior model development with private federated learning

Embodiments described herein provide for a non-transitory machine-readable medium storing instructions to cause one or more processors to receive, at a client device, a machine learning model from a server, detect a usage pattern for a content item, store an association between the content item and...

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Bibliographic Details
Main Authors Durocher, Alexis Hugo Louis, Bhowmick, Abhishek, Duchi, John, Freudiger, Julien, Do, Thi Hai Van, Kalu, Kalu Onuka, Gopalan, Sowmya, Chatzidakis, Michael, Tartavel, Guillaume, Cosman, Stephen, Rogers, Ryan M, Kapoor, Gaurav, Jagadeesh, Vignesh, Araujo, Marcelo Lotif
Format Patent
LanguageEnglish
Published 30.07.2024
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC COMMUNICATION TECHNIQUE
ELECTRIC DIGITAL DATA PROCESSING
ELECTRICITY
PHYSICS
TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION
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Summary:Embodiments described herein provide for a non-transitory machine-readable medium storing instructions to cause one or more processors to receive, at a client device, a machine learning model from a server, detect a usage pattern for a content item, store an association between the content item and the detected usage pattern in local data, train the machine learning model using local data for the content item with the detected usage pattern to generate a trained machine learning model, generate an update for the machine learning model, privatize the update for the machine learning model, and transmit the privatized update for the machine learning model to the server.
Bibliography:Application Number: US202017129579