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Unsupervised Domain Adaptation (UDA) makes predictions for the target domain data while manual annotations are only available in the source domain.
Dimensionality reduction by learning an invariant mapping
R. Hadsell, S. Chopra, and Y. LeCun · 2006
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Analysis of representations for domain adaptation
S. Ben-David, J. Blitzer, K. Crammer, and F. Pereira · 2007
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Visualizing data using t-sne
L. v. d. Maaten and G. Hinton · 2008
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Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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A theory of learning from different domains
S. Ben-David, J. Blitzer, K. Crammer, A. Kulesza, F. Pereira, and J. W. Vaughan · 2010
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Domain adaptation problems: A dasvm classification technique and a circular validation strategy
L. Bruzzone and M. Marconcini · 2010
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Adapting visual category models to new domains
K. Saenko, B. Kulis, M. Fritz, and T. Darrell · 2010
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Transfer feature learning with joint distribution adaptation
M. Long, J. Wang, G. Ding, J. Sun, and S. Y. Philip · 2013
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Equivalence of distance-based and rkhs-based statistics in hypothesis testing
D. Sejdinovic, B. Sriperumbudur, A. Gretton, and K. Fukumizu · 2013
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Easy samples first: Self-paced reranking for zero-example multimedia search
L. Jiang, D. Meng, T. Mitamura, and A. G. Hauptmann · 2014
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Deep domain confusion: Maximizing for domain invariance
E. Tzeng, J. Hoffman, N. Zhang, K. Saenko, and T. Darrell · 2014
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Unsupervised domain adaptation by backpropagation
Y. Ganin and V. Lempitsky · 2015
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Learning transferable features with deep adaptation networks
M. Long, Y. Cao, J. Wang, and M. I. Jordan · 2015
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Facenet: A unified embedding for face recognition and clustering
F. Schroff, D. Kalenichenko, and J. Philbin · 2015
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Domain separation networks
K. Bousmalis, G. Trigeorgis, N. Silberman, D. Krishnan, and D. Erhan · 2016
Cited alongside, same era.
Person re-identification by multi-channel parts-based cnn with improved triplet loss function
D. Cheng, Y. Gong, S. Zhou, J. Wang, and N. Zheng · 2016
Cited alongside, same era.
Domain-adversarial training of neural networks
Y. Ganin, E. Ustinova, H. Ajakan, P. Germain, H. Larochelle, F. Laviolette, M. Marchand, and V. Lempitsky · 2016
Cited alongside, same era.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Identity mappings in deep residual networks
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Cited alongside, same era.
Fcns in the wild: Pixel-level adversarial and constraint-based adaptation
J. Hoffman, D. Wang, F. Yu, and T. Darrell · 2016
Deep transfer learning with joint adaptation networks
M. Long, H. Zhu, J. Wang, and M. I. Jordan · 2017
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Visda: The visual domain adaptation challenge
X. Peng, B. Usman, N. Kaushik, J. Hoffman, D. Wang, and K. Saenko · 2017
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Adversarial discriminative domain adaptation
E. Tzeng, J. Hoffman, K. Saenko, and T. Darrell · 2017
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Bidirectional multirate reconstruction for temporal modeling in videos
L. Zhu, Z. Xu, and Y. Yang · 2017
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Self-ensembling for domain adaptation
G. French, M. Mackiewicz, and M. Fisher · 2018
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Shakeout: A new approach to regularized deep neural network training
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Cited alongside, same era.
Unsupervised domain adaptation with residual transfer networks
M. Long, H. Zhu, J. Wang, and M. I. Jordan · 2016
Cited alongside, same era.
Learning transferrable representations for unsupervised domain adaptation
O. Sener, H. O. Song, A. Saxena, and S. Savarese · 2016
Cited alongside, same era.
Deep coral: Correlation alignment for deep domain adaptation
B. Sun and K. Saenko · 2016
Cited alongside, same era.
Unsupervised pixel-level domain adaptation with generative adversarial networks
K. Bousmalis, N. Silberman, D. Dohan, D. Erhan, and D. Krishnan · 2017
Cited alongside, same era.
Associative domain adaptation
P. Haeusser, T. Frerix, A. Mordvintsev, and D. Cremers · 2017
Cited alongside, same era.
In defense of the triplet loss for person re-identification
A. Hermans, L. Beyer, and B. Leibe · 2017
Cited alongside, same era.
G. Kang, J. Li, and D. Tao · 2018
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Deep adversarial attention alignment for unsupervised domain adaptation: the benefit of target expectation maximization
G. Kang, L. Zheng, Y. Yan, and Y. Yang · 2018
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Multi-adversarial domain adaptation
Z. Pei, Z. Cao, M. Long, and J. Wang · 2018
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Adversarial dropout regularization
K. Saito, Y. Ushiku, T. Harada, and K. Saenko · 2018
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Maximum classifier discrepancy for unsupervised domain adaptation
K. Saito, K. Watanabe, Y. Ushiku, and T. Harada · 2018
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Visual domain adaptation with manifold embedded distribution alignment
J. Wang, W. Feng, Y. Chen, H. Yu, M. Huang, and P. S. Yu · 2018
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Searching for a robust neural architecture in four gpu hours
X. Dong and Y. Yang · 2019
Closest in time.
Taking a closer look at domain shift: Category-level adversaries for semantics consistent domain adaptation
Y. Luo, L. Zheng, T. Guan, J. Yu, and Y. Yang · 2019
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