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This paper explores the use of self-ensembling for visual domain adaptation problems.
Early stopping-but when?
Lutz Prechelt · 1998
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Zhi-Hua Zhou and Ming Li · 2005
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The German Traffic Sign Recognition Benchmark: A multi-class classification competition
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A kernel two-sample test
Arthur Gretton, Karsten M Borgwardt, Malte J Rasch, Bernhard Schölkopf, and Alexander Smola · 2012
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Microsoft COCO: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Deep domain confusion: Maximizing for domain invariance
Eric Tzeng, Judy Hoffman, Ning Zhang, Kate Saenko, and Trevor Darrell · 2014
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Unsupervised domain adaptation by backpropagation
Yaroslav Ganin and Victor Lempitsky · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Adam: A method for stochastic optimization
Diederik Kingma and Jimmy Ba · 2015
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Learning transferable features with deep adaptation networks
Mingsheng Long, Yue Cao, Jianmin Wang, and Michael Jordan · 2015
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Domain separation networks
Konstantinos Bousmalis, George Trigeorgis, Nathan Silberman, Dilip Krishnan, and Dumitru Erhan · 2016
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Deep reconstruction-classification networks for unsupervised domain adaptation
Muhammad Ghifary, W Bastiaan Kleijn, Mengjie Zhang, David Balduzzi, and Wen Li · 2016
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Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Revisiting batch normalization for practical domain adaptation
Yanghao Li, Naiyan Wang, Jianping Shi, Jiaying Liu, and Xiaodi Hou · 2016
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Regularization with stochastic transformations and perturbations for deep semi-supervised learning
Mehdi Sajjadi, Mehran Javanmardi, and Tolga Tasdizen · 2016
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Virtual adversarial training: a regularization method for supervised and semi-supervised learning
Takeru Miyato, Schi-ichi Maeda, Masanori Koyama, and Shin Ishii · 2017
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From source to target and back: symmetric bi-directional adaptive gan
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Asymmetric tri-training for unsupervised domain adaptation
Kuniaki Saito, Yoshitaka Ushiku, and Tatsuya Harada · 2017
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Baochen Sun and Kate Saenko · 2016
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Discrepancy-based networks for unsupervised domain adaptation: A comparative study
Gabriela Csurka, Fabien Baradel, Boris Chidlovskii, and Stephane Clinchant · 2017
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Associative domain adaptation
Philip Haeusser, Thomas Frerix, Alexander Mordvintsev, and Daniel Cremers · 2017
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Kuniaki Saito, Yoshitaka Ushiku, Tatsuya Harada, and Kate Saenko · 2017
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Swami Sankaranarayanan, Yogesh Balaji, Carlos D Castillo, and Rama Chellappa · 2017
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