Title:
FEDERATED LEARNING MODELING OPTIMIZATION METHOD AND DEVICE, AND READABLE STORAGE MEDIUM AND PROGRAM PRODUCT
Document Type and Number:
WIPO Patent Application WO/2023/005133
Kind Code:
A1
Abstract:
Disclosed in the present application are a federated learning modeling optimization method and device, and a readable storage medium and a program product, which are applied to a federated server. The federated learning modeling optimization method comprises: distributing initial global feature extraction models corresponding to data modals to participant devices corresponding to the data modals, so that the participant devices obtain globally optimized local feature extraction models on the basis of local private training samples and by means of contrastive learning training, and generate target modal public sample representations according to the globally optimized local feature extraction models; receiving the target modal public sample representations sent by the participant devices, and aggregating the target modal public sample representations into target modal aggregated sample representations; and according to training samples selected from a public data set, optimizing each initial model global feature extraction model into a corresponding target global feature extraction model by means of knowledge distillation and contrastive learning.
Inventors:
HE YUANQIN (CN)
Application Number:
PCT/CN2021/141481
Publication Date:
February 02, 2023
Filing Date:
December 27, 2021
Export Citation:
Assignee:
WEBANK CO LTD (CN)
International Classes:
G06N20/20
Foreign References:
| CN113516255A | 2021-10-19 | |||
| CN113128701A | 2021-07-16 | |||
| CN112651511A | 2021-04-13 | |||
| US20180373988A1 | 2018-12-27 | |||
| CN112101578A | 2020-12-18 | |||
| CN111144579A | 2020-05-12 |
Attorney, Agent or Firm:
CENFO INTELLECTUAL PROPERTY AGENCY (CN)
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