Method and device for jointly updating business models

A business model and service-side technology, applied in the field of privacy protection, can solve problems such as data increase, affect the overall training efficiency, and communication congestion, and achieve the effects of improving efficiency, avoiding communication congestion, and reducing communication traffic

Active Publication Date: 2022-05-27
ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Especially in some scenarios where there are many training members participating in federated learning, the data received by the server increases geometrically, which may cause communication congestion and seriously affect the overall training efficiency

Method used

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  • Method and device for jointly updating business models
  • Method and device for jointly updating business models
  • Method and device for jointly updating business models

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Embodiment Construction

[0039] The solution provided in this specification will be described below with reference to the accompanying drawings.

[0040] Federated learning, also known as federated machine learning, federated learning, federated learning, etc. Federated Machine Learning is a machine learning framework that can effectively help multiple agencies conduct data usage and machine learning modeling while meeting user privacy protection, data security, and government regulations.

[0041] Specifically, it is assumed that enterprise A and enterprise B each establish a task model, and a single task can be classification or prediction, and these tasks have also been approved by their respective users when obtaining data. However, due to incomplete data, for example, enterprise A lacks label data, enterprise B lacks user feature data, or the data is insufficient and the sample size is not enough to establish a good model, the model at each end may not be established or the effect may not be idea...

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PUM

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Abstract

The embodiment of this specification provides a method and device for jointly updating a business model based on privacy protection, wherein, in an iterative process, the service provider provides global model parameters to each data party, and N Each data party uses the global model parameters to update the local business model, and further updates the updated local business model based on the local business data, so that the model of each corresponding parameter group in the new business model The parameters are uploaded to the server, and then the server sequentially fuses the received parameter groups to update the global model parameters. This process can reduce the communication pressure between the data side and the server side, avoid communication congestion, and help improve the overall training efficiency of federated learning.

Description

technical field [0001] One or more embodiments of this specification relate to the field of computer technology, and in particular, to a method and apparatus for jointly updating a business model based on privacy protection. Background technique [0002] The development of computer technology has made machine learning more and more widely used in various business scenarios. Federated learning is a method for joint modeling while preserving private data. For example, cooperative security modeling is required between enterprises, and federated learning can be used to collaboratively train data processing models using data from all parties under the premise of fully protecting enterprise data privacy, so that data processing models can be processed more accurately and efficiently. business data. In a federated learning scenario, for example, all parties can agree on a model structure (or an agreed model), then use private data to train locally, and use a safe and reliable met...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06N20/00G06N3/08G06N3/04G06F21/62G06F21/60
CPCG06N20/00G06N3/08G06F21/6245G06F21/602G06N3/045
Inventor 郑龙飞陈超超王力张本宇
Owner ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
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