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cs.LG2025
Soft Separation and Distillation: Toward Global Uniformity in Federated Unsupervised Learning
Hung-Chieh Fang, Hsuan-Tien Lin, Irwin King +1
Federated Unsupervised Learning (FUL) aims to learn expressive representations in federated and self-supervised settings. The quality of representations learned in FUL is usually d…
cs.LG2024
Tackling Dimensional Collapse toward Comprehensive Universal Domain Adaptation
Hung-Chieh Fang, Po-Yi Lu, Hsuan-Tien Lin
Universal Domain Adaptation (UniDA) addresses unsupervised domain adaptation where target classes may differ arbitrarily from source ones, except for a shared subset. A widely used…