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Conventional unsupervised domain adaptation (UDA) methods need to access both labeled source samples and unlabeled target samples simultaneously to train the model.
Gradient-based learning applied to document recognition
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A theory of learning from different domains
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Discriminative Clustering by Regularized Information Maximization
Gomes, R.; Krause, A.; and Perona, P. 2010 · 2010
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A Survey on Transfer Learning
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Generative Adversarial Networks
Goodfellow, I. J.; Pouget-Abadie, J.; et al. 2014 · 2014
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Unsupervised domain adaptation by backpropagation
Ganin, Y.; and Lempitsky, V. 2015 · 2015
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Learning Transferable Features with Deep Adaptation Networks
Long, M.; Cao, Y.; Wang, J.; and Jordan, M. I. 2015 · 2015
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Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Ren, S.; He, K.; Girshick, R. B.; and Sun, J. 2015 · 2015
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Domain-Adversarial Training of Neural Networks
Ganin, Y.; Ustinova, E.; Ajakan, H.; Germain, P.; Larochelle, H.; Laviolette, F.; Marchand, M.; and Lempitsky, V. S. 2016 · 2016
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Deep Residual Learning for Image Recognition
He, K.; Zhang, X.; et al. 2016 · 2016
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Return of Frustratingly Easy Domain Adaptation
Sun, B.; Feng, J.; and Saenko, K. 2016 · 2016
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Deep Transfer Learning with Joint Adaptation Networks
Long, M.; Zhu, H.; Wang, J.; and Jordan, M. I. 2017 · 2017
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VisDA: The Visual Domain Adaptation Challenge
Peng, X.; Usman, B.; et al. 2017 · 2017
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Asymmetric Tri-training for Unsupervised Domain Adaptation
Saito, K.; Ushiku, Y.; and Harada, T. 2017 · 2017
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Adversarial Discriminative Domain Adaptation
Tzeng, E.; Hoffman, J.; Saenko, K.; and Darrell, T. 2017 · 2017
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Deep Hashing Network for Unsupervised Domain Adaptation
Venkateswara, H.; Eusebio, J.; et al. 2017 · 2017
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Central Moment Discrepancy (CMD) for Domain-Invariant Representation Learning
Zellinger, W.; Grubinger, T.; Lughofer, E.; Natschläger, T.; and Saminger-Platz, S. 2017 · 2017
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CyCADA: Cycle-Consistent Adversarial Domain Adaptation
Hoffman, J.; Tzeng, E.; et al. 2018 · 2018
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Co-regularized Alignment for Unsupervised Domain Adaptation
Kumar, A.; Sattigeri, P.; Wadhawan, K.; Karlinsky, L.; Feris, R.; Freeman, W.; and Wornell, G. 2018 · 2018
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Learning without Forgetting
Li, Z.; and Hoiem, D. 2018 · 2018
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Conditional adversarial domain adaptation
Long, M.; Cao, Z.; et al. 2018 · 2018
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Adversarial Dropout Regularization
Saito, K.; Ushiku, Y.; Harada, T.; and Saenko, K. 2018 · 2018
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Maximum classifier discrepancy for unsupervised domain adaptation
Saito, K.; Watanabe, K.; et al. 2018 · 2018
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Wasserstein Distance Guided Representation Learning for Domain Adaptation
Shen, J.; Qu, Y.; Zhang, W.; and Yu, Y. 2018 · 2018
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PANDA: Prototypical Unsupervised Domain Adaptation
Hu, D.; Liang, J.; et al. 2020 · 2020
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Minimum Class Confusion for Versatile Domain Adaptation
Jin, Y.; Wang, X.; et al. 2020 · 2020
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Progressive Domain Adaptation from a Source Pre-trained Model
Kim, Y.; Cho, D.; et al. 2020 · 2020
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Universal Source-Free Domain Adaptation
Kundu, J. N.; Venkat, N.; RahulM., V.; and Babu, R. V. 2020 · 2020
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Maximum Density Divergence for Domain Adaptation
Li, J.; Chen, E.; Ding, Z.; Zhu, L.; Lu, K.; and Shen, H. T. 2020 · 2020
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Model adaptation: Unsupervised domain adaptation without source data
Li, R.; Jiao, Q.; et al. 2020 · 2020
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mixup: Beyond Empirical Risk Minimization
Zhang, H.; Cissé, M.; Dauphin, Y.; and Lopez-Paz, D. 2018 · 2018
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Unsupervised Domain Adaptation via Regularized Conditional Alignment
Cicek, S.; and Soatto, S. 2019 · 2019
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Cluster Alignment With a Teacher for Unsupervised Domain Adaptation
Deng, Z.; Luo, Y.; and Zhu, J. 2019 · 2019
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Contrastive Adaptation Network for Unsupervised Domain Adaptation
Kang, G.; Jiang, L.; et al. 2019 · 2019
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Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation
Lee, C.-Y.; Batra, T.; Baig, M. H.; and Ulbricht, D. 2019b · 2019
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When Does Label Smoothing Help?
Müller, R.; Kornblith, S.; et al. 2019 · 2019
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Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation
Liang, J.; Hu, D.; et al. 2020 · 2020
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Unsupervised Intra-Domain Adaptation for Semantic Segmentation Through Self-Supervision
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Unsupervised Domain Adaptation via Structurally Regularized Deep Clustering
Tang, H.; Chen, K.; and Jia, K. 2020 · 2020
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Bi-Directional Generation for Unsupervised Domain Adaptation
Yang, G.; Xia, H.; et al. 2020 · 2020
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Unsupervised Domain Adaptation without Source Data by Casting a BAIT
Yang, S.; Wang, Y.; et al. 2020 · 2020
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Unsupervised Multi-source Domain Adaptation Without Access to Source Data
Ahmed, S. M.; Raychaudhuri, D. S.; Paul, S.; Oymak, S.; and Roy-Chowdhury, A. 2021 · 2021
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KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation
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Domain Impression: A Source Data Free Domain Adaptation Method
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A Free Lunch for Unsupervised Domain Adaptive Object Detection without Source Data
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Source-Free Domain Adaptation for Semantic Segmentation
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Source-free Domain Adaptation via Avatar Prototype Generation and Adaptation
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Source-Free Open Compound Domain Adaptation in Semantic Segmentation
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