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Gotta Adapt 'Em All: Joint Pixel and Feature-Level Domain Adaptation for Recognition in the Wild.

, , , , and . CVPR, page 2672-2681. Computer Vision Foundation / IEEE, (2019)

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Online Incremental Feature Learning with Denoising Autoencoders., , and . AISTATS, volume 22 of JMLR Proceedings, page 1453-1461. JMLR.org, (2012)An interpretation of the Cover and Leung capacity region for the MAC with feedback through stochastic control., and . ICC, page 2360-2364. IEEE, (2012)Active Adversarial Domain Adaptation., , , , , and . CVPR Workshops, page 1-4. Computer Vision Foundation / IEEE, (2019)Improved Deep Metric Learning with Multi-class N-pair Loss Objective.. NIPS, page 1849-1857. (2016)Improved Multimodal Deep Learning with Variation of Information., , and . NIPS, page 2141-2149. (2014)Unifying Distribution Alignment as a Loss for Imbalanced Semi-supervised Learning., , , , , and . WACV, page 5633-5642. IEEE, (2023)Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types., , , , and . WACV, page 5468-5479. IEEE, (2023)Learning and Evaluating Representations for Deep One-class Classification., , , , and . CoRR, (2020)Text Prompting for Multi-Concept Video Customization by Autoregressive Generation., , , , , and . CoRR, (2024)i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning., , , , , and . ICLR, OpenReview.net, (2021)