67 citations · 91 across the 6 of their papers we have counts for
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cs.LG2025
Efficient Test-Time Adaptation through Latent Subspace Coefficients Search
Xinyu Luo, Jie Liu, Kecheng Chen +6
Real-world deployment often exposes vision models to distribution shifts, making test-time adaptation (TTA) important for reliable prediction. Existing TTA methods can be difficult…
cs.LG2023
Target-agnostic Source-free Domain Adaptation for Regression Tasks
Tianlang He, Zhiqiu Xia, Jierun Chen +2
Unsupervised domain adaptation (UDA) seeks to bridge the domain gap between the target and source using unlabeled target data. Source-free UDA removes the requirement for labeled s…
cs.LG2022★ 67 cited
Domain-invariant Feature Exploration for Domain Generalization
Wang Lu, Jindong Wang, Haoliang Li +2
Deep learning has achieved great success in the past few years. However, the performance of deep learning is likely to impede in face of non-IID situations. Domain generalization (…