Invention Publication
- Patent Title: CUSTOMIZABLE FEDERATED LEARNING
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Application No.: US17843264Application Date: 2022-06-17
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Publication No.: US20230409983A1Publication Date: 2023-12-21
- Inventor: Srinivas Siva Kumar Aradhyula , Eugenia Kim , Myungjin Lee , Ali Payani
- Applicant: Cisco Technology, Inc.
- Applicant Address: US CA San Jose
- Assignee: Cisco Technology, Inc.
- Current Assignee: Cisco Technology, Inc.
- Current Assignee Address: US CA San Jose
- Main IPC: G06N20/20
- IPC: G06N20/20 ; H04L67/10 ; H04L67/52

Abstract:
In one embodiment, a controller for a federated learning system identifies a first dataset and a second dataset available to a particular node of the federated learning system. The first dataset comprises features that are common to all nodes of the federated learning system. The second dataset comprises features that are common only to a subset of nodes of the federated learning system. The controller configures the particular node to train a first model using the first dataset. The controller causes formation of a global model in the federated learning system that aggregates the first model from the particular node with models from all other nodes of the federated learning system. The controller configures the particular node to train a second model using the second dataset.
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