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Margin-aware Adversarial Domain Adaptation with Optimal Transport.

, , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 2514-2524. PMLR, (2020)

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Deep Neural Networks Are Congestion Games: From Loss Landscape to Wardrop Equilibrium and Beyond., , and . CoRR, (2020)POT: Python Optimal Transport., , , , , , , , , and 12 other author(s). J. Mach. Learn. Res., (2021)Feature Selection for Unsupervised Domain Adaptation Using Optimal Transport., , and . ECML/PKDD (2), volume 11052 of Lecture Notes in Computer Science, page 759-776. Springer, (2018)Non-negative embedding for fully unsupervised domain adaptation., and . Pattern Recognit. Lett., (2016)Leveraging Ensemble Diversity for Robust Self-Training in the Presence of Sample Selection Bias., , and . CoRR, (2023)Unbalanced CO-optimal Transport., , , , , , and . AAAI, page 10006-10016. AAAI Press, (2023)Putting Theory to Work: From Learning Bounds to Meta-Learning Algorithms., , , , and . CoRR, (2020)Random subspaces NMF for unsupervised transfer learning., and . IJCNN, page 3901-3908. IEEE, (2014)Revisiting (\epsilon, \gamma, \tau)-similarity learning for domain adaptation., and . NeurIPS, page 7408-7417. (2018)Margin-aware Adversarial Domain Adaptation with Optimal Transport., , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 2514-2524. PMLR, (2020)