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Minimum Class Confusion for Versatile Domain Adaptation.

, , , and . ECCV (21), volume 12366 of Lecture Notes in Computer Science, page 464-480. Springer, (2020)

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Regressive Domain Adaptation for Unsupervised Keypoint Detection., , , , , and . CVPR, page 6780-6789. Computer Vision Foundation / IEEE, (2021)CLIPood: Generalizing CLIP to Out-of-Distributions., , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 31716-31731. PMLR, (2023)Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation., , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 7124-7133. PMLR, (2019)ForkMerge: Overcoming Negative Transfer in Multi-Task Learning., , , , , , and . CoRR, (2023)Bi-tuning of Pre-trained Representations., , , , and . CoRR, (2020)Bi-tuning: Efficient Transfer from Pre-trained Models., , , , and . ECML/PKDD (5), volume 14173 of Lecture Notes in Computer Science, page 357-373. Springer, (2023)Decoupled Training: Return of Frustratingly Easy Multi-Domain Learning., , , , and . AAAI, page 15644-15652. AAAI Press, (2024)X-model: Improving Data Efficiency in Deep Learning with A Minimax Model., , , and . ICLR, OpenReview.net, (2022)Ad Recommendation in a Collapsed and Entangled World., , , , , , , , , and . CoRR, (2024)Minimum Class Confusion for Versatile Domain Adaptation., , , and . ECCV (21), volume 12366 of Lecture Notes in Computer Science, page 464-480. Springer, (2020)