Invention Publication
- Patent Title: FEDERATED LEARNING SURROGATION WITH TRUSTED SERVER
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Application No.: US17932809Application Date: 2022-09-16
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Publication No.: US20240095513A1Publication Date: 2024-03-21
- Inventor: Jian SHEN , Jamie Menjay LIN
- Applicant: QUALCOMM Incorporated
- Applicant Address: US CA San Diego
- Assignee: QUALCOMM Incorporated
- Current Assignee: QUALCOMM Incorporated
- Current Assignee Address: US CA San Diego
- Main IPC: G06N3/08
- IPC: G06N3/08

Abstract:
Certain aspects of the present disclosure provide techniques and apparatus for surrogated federated learning. A set of intermediate activations is received at a trusted server from a node device, where the node device generated the set of intermediate activations using a first set of layers of a neural network. One or more weights associated with a second set of layers of the neural network are refined using the set of intermediate activations, and one or more weight updates corresponding to the refined one or more weights are transmitted to a federated learning system.
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