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Title:
MACHINE LEARNING SYSTEM AND MACHINE LEARNING METHOD
Document Type and Number:
WIPO Patent Application WO/2023/139820
Kind Code:
A1
Abstract:
This machine learning system includes: a server that holds a common model; and a plurality of clients, each of which holds data being concealed and an individual model. The server transmits the common model to the plurality of clients. Each of the plurality of clients generates a learning result of updating the common model, on the basis of the data being concealed and the individual model held by the client, and transmits the generated learning result to the server. The server updates the common model on the basis of the received learning results.

Inventors:
KAGA YOSUKE (JP)
TAKAHASHI KENTA (JP)
NAKAMURA WATARU (JP)
SUZUKI YUSEI (JP)
Application Number:
PCT/JP2022/030793
Publication Date:
July 27, 2023
Filing Date:
August 12, 2022
Export Citation:
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Assignee:
HITACHI LTD (JP)
International Classes:
G06F21/32; G06N20/00; G06F21/62
Foreign References:
CN110399742A2019-11-01
Other References:
MANOJ GHUHAN ARIVAZHAGAN; VINAY AGGARWAL; AADITYA KUMAR SINGH; SUNAV CHOUDHARY: "Federated Learning with Personalization Layers", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 2 December 2019 (2019-12-02), 201 Olin Library Cornell University Ithaca, NY 14853 , XP081543392
HOSSEIN HOSSEINI; HYUNSIN PARK; SUNGRACK YUN; CHRISTOS LOUIZOS; JOSEPH SORIAGA; MAX WELLING: "Federated Learning of User Verification Models Without Sharing Embeddings", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 7 June 2021 (2021-06-07), 201 Olin Library Cornell University Ithaca, NY 14853 , XP081939772
Attorney, Agent or Firm:
TOU-OU PATENT FIRM (JP)
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