Invention Grant
- Patent Title: Localized learning from a global model
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Application No.: US17082730Application Date: 2020-10-28
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Publication No.: US11551153B2Publication Date: 2023-01-10
- Inventor: Daniel Ramage , Jeremy Gillmor Kahn
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Fish & Richardson P.C.
- Main IPC: G06N20/00
- IPC: G06N20/00 ; H04L67/01

Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for obtaining a global model for a particular activity, the global model derived based on input data representing multiple observations associated with the particular activity performed by a collection of users; determining, using the global model, expected data representing an expected observation associated with the particular activity performed by a particular user; receiving, by a computing device operated by the particular user, particular data representing an actual observation associated with the particular activity performed by the particular user; determining, by the computing device and using (i) the expected data and (ii) the particular data, residual data of the particular user; and deriving a local model of the particular user based on the residual data.
Public/Granted literature
- US20210042666A1 Localized Learning From A Global Model Public/Granted day:2021-02-11
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