Method and device for generating sample data

Abstract

The invention relates to the field of artificial intelligence, and discloses a method and a device for generating sample data. The method comprises the steps of acquiring an initial predictor model, andconducting the iterative optimization on the predictor model through multiple rounds of iterative operation, wherein the predictor model represents the relation between training sample data and theperformance of a neural network model trained based on the training sample data; in response to determining that the iteratively optimized predictor model reaches a preset convergence condition, generating target sample data by using the iteratively optimized predictor model; wherein the iterative operation comprises the following steps: predicting training sample data corresponding to a neural network model with preset performance as current sample data by adopting a current predictor model; training a preset neural network model based on the current sample data, and obtaining the actual performance of the trained preset neural network model; and updating the parameters of the predictor model according to the deviation between the preset performance and the actual performance. According to the method, the sample data of the neural network model with good training performance can be obtained.

Description

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AI Technical Summary

Benefits of technology

This invention allows for automatic determination of how well an artificial intelligence system works by learning from experience or testing it on new samples instead of manually creating them yourself.

Problems solved by technology

This patented technical problem addressed by this patents relates to improving the efficiency at which deep learning models can be trained for various applications such as image processing or speech recognition due to limitations associated with selecting suitable samples during training time. Current methods often result in overfitting certain types of datasets that are more effective than others when used alone.

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