Self-training is widely used in unsupervised domain adaptation (UDA) by assigning pseudo labels to unlabeled samples. However, existing self-training strategies bring bias, while potentially ...

Abstract: In the realm of stock market prediction, traditional supervised learning approaches often struggle with the vast and diverse nature of financial data, coupled with privacy concerns. This ...