Papers › Make the U in UDA Matter: Invariant Consistency Learning for Unsupervised Domain Adaptation

Make the U in UDA Matter: Invariant Consistency Learning for Unsupervised Domain Adaptation

22 Sep 2023NeurIPS 2023 11arXiv:2309.12742archive 2025-07-28

Zhongqi Yue, Hanwang Zhang, Qianru Sun

Domain Adaptation (DA) is always challenged by the spurious correlation between domain-invariant features (e.g., class identity) and domain-specific features (e.g., environment) that does not generalize to the target domain. Unfortunately, even enriched with additional unsupervised target domains, existing Unsupervised DA (UDA) methods still suffer from it. This is because the source domain supervision only considers the target domain samples as auxiliary data (e.g., by pseudo-labeling), yet the inherent distribution in the target domain -- where the valuable de-correlation clues hide -- is disregarded. We propose to make the U in UDA matter by giving equal status to the two domains. Specifically, we learn an invariant classifier whose prediction is simultaneously consistent with the labels in the source domain and clusters in the target domain, hence the spurious correlation inconsistent in the target domain is removed. We dub our approach "Invariant CONsistency learning" (ICON). Extensive experiments show that ICON achieves the state-of-the-art performance on the classic UDA benchmarks: Office-Home and VisDA-2017, and outperforms all the conventional methods on the challenging WILDS 2.0 benchmark. Codes are in https://github.com/yue-zhongqi/ICON.

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EqInv yue-zhongqi/icon/icon/eqinv.py official repository ran MIT (permissive) · 05d5fa3202581544 · report
SupConLoss yue-zhongqi/icon/icon/eqinv.py official repository ran MIT (permissive) · 9e503ad659734ce5 · report
entropy yue-zhongqi/ICON/icon/entropy.py official repository ran MIT (permissive) · 410274324074f68f · report
reduce_dimension yue-zhongqi/ICON/icon/cluster.py official repository ran MIT (permissive) · 24d03f510ae465bf · report
shift_log yue-zhongqi/ICON/icon/uda_backbone.py official repository ran fingerprinted MIT (permissive) · e1deb74aab00d687 · report
translate_x_rel yue-zhongqi/ICON/icon/randaugment.py official repository ran MIT (permissive) · a4b471197204b414 · report
PairEnum yue-zhongqi/ICON/icon/cluster.py official repository unverified MIT (permissive) · b7a6bc2d6ab2911e · report
shear_x yue-zhongqi/ICON/icon/randaugment.py official repository unverified MIT (permissive) · 7b4e3d0bd192b677 · report
shear_y yue-zhongqi/ICON/icon/randaugment.py official repository unverified MIT (permissive) · e31c4b500a240e69 · report

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Domain AdaptationUnsupervised Domain Adaptation

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