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The learning of domain-invariant representations in the context of domain adaptation with neural networks is considered.
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Bharath K Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Gert RG Lanckriet, and Bernhard Schölkopf · 2009
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Adaptive subgradient methods for online learning and stochastic optimization
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Domain adaptation for large-scale sentiment classification: A deep learning approach
Xavier Glorot, Antoine Bordes, and Yoshua Bengio · 2011
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Domain adaptation via transfer component analysis
Sinno Jialin Pan, Ivor W Tsang, James T Kwok, and Qiang Yang · 2011
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Marginalized denoising autoencoders for domain adaptation
Minmin Chen, Zhixiang Xu, Kilian Weinberger, and Fei Sha · 2012
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The smallest upper bound for the pth absolute central moment of a class of random variables
Martin Egozcue, Luis Fuentes García, Wing Keung Wong, and Ricardas Zitikis · 2012
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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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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Adadelta: an adaptive learning rate method
Matthew D Zeiler · 2012
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Convergence of probability measures
Patrick Billingsley · 2013
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Dlid: Deep learning for domain adaptation by interpolating between domains
Sumit Chopra, Suhrid Balakrishnan, and Raghuraman Gopalan · 2013
Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Generative moment matching networks
Yujia Li, Kevin Swersky, and Richard Zemel · 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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Fastmmd: Ensemble of circular discrepancy for efficient two-sample test
Ji Zhao and Deyu Meng · 2015
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Supervised representation learning: Transfer learning with deep autoencoders
Fuzhen Zhuang, Xiaohu Cheng, Ping Luo, Sinno Jialin Pan, and Qing He · 2015
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Domain-adversarial training of neural networks
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Unsupervised domain adaptation by domain invariant projection
Yujia Li, Kevin Swersky, and Richard Zemel · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 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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Landmarks-based kernelized subspace alignment for unsupervised domain adaptation
Rahaf Aljundi, Rémi Emonet, Damien Muselet, and Marc Sebban · 2015
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Keras: Deep learning library for theano and tensorflow, 2015
François Chollet · 2015
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Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, and Victor Lempitsky · 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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The variational fair auto encoder
Christos Louizos, Kevin Swersky, Yujia Li, Max Welling, and Richard Zemel · 2016
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Deep coral: Correlation alignment for deep domain adaptation
Baochen Sun and Kate Saenko · 2016
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Return of frustratingly easy domain adaptation
Baochen Sun, Jiashi Feng, and Kate Saenko · 2016
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Generative models and model criticism via optimized maximum mean discrepancy
Dougal J Sutherland, Hsiao-Yu Tung, Heiko Strathmann, Soumyajit De, Aaditya Ramdas, Alex Smola, and Arthur Gretton · 2016
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