Research on unlabeled target domain adaptive information processing based on TrAdaBoost algorithm

Lulu Dong; Chen Sun

doi:10.1117/12.2683294

26 June 2023 Research on unlabeled target domain adaptive information processing based on TrAdaBoost algorithm

Lulu Dong, Chen Sun

Proceedings Volume 12714, International Conference on Computer Network Security and Software Engineering (CNSSE 2023); 127141N (2023) https://doi.org/10.1117/12.2683294
Event: Third International Conference on Computer Network Security and Software Engineering (CNSSE 2023), 2023, Sanya, China

Abstract

In recent years, information processing technology based on transfer learning has developed rapidly, and more and more data users do have not enough time to complete data labeling. Domain Adaptation (DA) information processing for unlabeled data is becoming increasingly important. To improve the performance of the model in the target domain information processing, we design a target domain information network and propose a collaborative learning model between the private network and the regional adaptive network based on the TrAdaBoost algorithm. Different from the traditional method, this model can avoid directly reducing the difference between domains as the model optimization goal, and the target is optimized for cluster regularization, driving the target domain data points closer to the cluster center. And further, promote the training of domain information networks. Through simulation experiments, it is concluded that under this model, the target domain private network is effectively trained based on the TrAdaBoost algorithm under the specified target domain, to achieve better information processing performance in the target domain.

Citation Download Citation

Lulu Dong and Chen Sun "Research on unlabeled target domain adaptive information processing based on TrAdaBoost algorithm", Proc. SPIE 12714, International Conference on Computer Network Security and Software Engineering (CNSSE 2023), 127141N (26 June 2023); https://doi.org/10.1117/12.2683294

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