Title:
MODEL TRAINING METHOD AND APPARATUS FOR PRIVATE DATA SET
Document Type and Number:
WIPO Patent Application WO/2023/050754
Kind Code:
A1
Abstract:
A private data set-based method and apparatus for model training, which relate to the technical field of multi-party data collaboration. The method comprises: training a server-side model on the basis of a public data set and a real label corresponding to the public data set; obtaining first model outputs sent by clients, the first model outputs being obtained by inputting the public data set into local learning models, and the local learning models being obtained by training on the basis of the private data set and the corresponding label; training the server-side model on the basis of public data corresponding to the first model outputs; inputting the public data set into the server-side model to obtain second model outputs; and sending the second model outputs to the clients, for the clients to perform retraining of the local learning models on the basis of the second model outputs and the public data set. As such, while avoiding private data set leakage, model training is performed by using the private data set as part of training samples on the basis of knowledge distillation and knowledge fusion.
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Inventors:
LIU YANG (CN)
LIU YANG (CN)
LIU YANG (CN)
Application Number:
PCT/CN2022/085131
Publication Date:
April 06, 2023
Filing Date:
April 02, 2022
Export Citation:
Assignee:
UNIV TSINGHUA (CN)
International Classes:
G06F21/62
Foreign References:
| CN114003949A | 2022-02-01 | |||
| CN113222175A | 2021-08-06 | |||
| CN113052334A | 2021-06-29 | |||
| US20210272011A1 | 2021-09-02 |
Attorney, Agent or Firm:
CN-KNOWHOW INTELLECTUAL PROPERTY AGENT LIMITED (CN)
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