Design method and device of federation learning mechanism and storage medium

Abstract

The invention discloses a design method of a federation learning mechanism. The method comprises the steps of configuring a preset calculation graph; obtaining a selectable optimization target; configuring a loss function for the preset calculation graph according to the selectable optimization target, and obtaining a calculation graph configured with the loss function; acquiring data validity prior distribution data and participant type prior distribution data; generating random training data according to the data validity prior distribution data and the participant type prior distribution data; training the calculation graph configured with the loss function according to the random training data to obtain an optimal training parameter; and obtaining the federation learning mechanism according to the optimal training parameters and the preset calculation graph. The invention further discloses a design device of the federation learning mechanism and a computer readable storage medium.According to the invention, the convenience of federation learning mechanism calculation can be improved.

Description

technical field [0001] The present invention relates to the field of mechanism design, in particular to a design method, device and computer-readable storage medium of a federated learning mechanism. Background technique [0002] Federated learning, also known as federated machine learning, is a machine learning framework that can effectively help multiple organizations perform data usage and machine learning modeling while meeting the requirements of user privacy protection, data security, and government regulations. Federated learning allows multiple data providers to jointly model and can solve the problem of data isolation. At present, federated learning needs to design an incentive mechanism, that is, to determine an optimal social selection function, which is used to meet the premise of incentive compatibility, individual rationality, budget balance, social welfare maximization and fairness in the mechanism. Under this circumstance, different economic incentives are p...

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Problems solved by technology

[0003] But at present, in the existing technology, the design process of the federated learning incentive mechanism, that is, the process of determining the optimal social choice function, still relies on the experience and intuition of senior mechanism design experts, which will not only result in inaccurate design results, but also require A certain amount of human and mental work has limitations

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