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We propose associative domain adaptation, a novel technique for end-to-end domain adaptation with neural networks, the task of inferring class labels for an unlabeled target domain based on the statistical properties of a labeled source domain.
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Generative adversarial nets
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J. Yosinski, J. Clune, Y. Bengio, and H. Lipson · 2014
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K. Bousmalis, G. Trigeorgis, N. Silberman, D. Krishnan, and D. Erhan · 2016
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Y. Ganin, E. Ustinova, H. Ajakan, P. Germain, H. Larochelle, F. Laviolette, M. Marchand, and V. Lempitsky · 2016
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Beyond sharing weights for deep domain adaptation
A. Rozantsev, M. Salzmann, and P. Fua · 2016
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Learning transferrable representations for unsupervised domain adaptation
O. Sener, H. O. Song, A. Saxena, and S. Savarese · 2016
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Flownet: Learning optical flow with convolutional networks
A. Dosovitskiy, P. Fischer, E. Ilg, P. Hausser, C. Hazirbas, V. Golkov, P. van der Smagt, D. Cremers, and T. Brox · 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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Imagenet large scale visual recognition challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and L. Fei-Fei · 2015
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Going deeper with convolutions
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich · 2015
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Unsupervised pixel-level domain adaptation with generative adversarial networks
K. Bousmalis, N. Silberman, D. Dohan, D. Erhan, and D. Krishnan · 2016
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B. Sun, J. Feng, and K. Saenko · 2016
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Deep coral: Correlation alignment for deep domain adaptation
B. Sun and K. Saenko · 2016
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Generative models and model criticism via optimized maximum mean discrepancy
D. J. Sutherland, H.-Y. Tung, H. Strathmann, S. De, A. Ramdas, A. Smola, and A. Gretton · 2016
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Adversarial discriminative domain adaptation
E. Tzeng, J. Hoffman, K. Saenko, and T. Darrell · 2016
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How to use t-sne effectively
M. Wattenberg, F. Viégas, and I. Johnson · 2016
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Learning by association - a versatile semi-supervised training method for neural networks
P. Haeusser, A. Mordvintsev, and D. Cremers · 2017
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