Author

Yi Xiang

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Preprint Aug 2026

Joint Distribution Alignment for Universal Domain Adaptation

An upper bound of the generalization error for universal domain adaptation is provided and a novel UniDA algorithm called Joint Distribution Alignment for Universal Domain Adaptation (JAUA), which aligns the joint distributions by minimizing the distribution discrepancy calculated by Chi-Square divergence is proposed.

Shi-Zhe Li, Hongshan Pu, Mengying Xie et al. · 0 citations

Conference Open access Sep 2026

Progressive Adversarial Multi-View Alignment for Unsupervised Embedded Feature Selection with Linear Complexity

A Progressive Adversarial Feature Selection (ProAd-FS) framework for large-scale multi-view learning is proposed, which formulates this static trade-off objective as a dynamic competitive process and achieves state-of-the-art performance while being highly scalable as well.

Shi-Xuan Zhou, Yi Xiang, Hao-Xiang Qin et al. · Proceedings of the Thirty-Fi... · 0 citations