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We investigate the power of censoring techniques, first developed for learning {\em fair representations}, to address domain generalization.
A theory of learning from different domains
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Undoing the damage of dataset bias
Aditya Khosla, Tinghui Zhou, Tomasz Malisiewicz, Alexei A Efros, and Antonio Torralba · 2012
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Domain generalization via invariant feature representation
Krikamol Muandet, David Balduzzi, and Bernhard Schölkopf · 2013
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Learning fair representations
Richard Zemel, Kevin Swersky, Toniann Pitassi, and Cynthia Dwork · 2013
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Exploiting low-rank structure from latent domains for domain generalization
Zheng Xu, Wen Li, Li Niu, and Dong Xu · 2014
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Censoring Representations with an Adversary
Harrison Edwards and Amos Storkey · 2015
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Domain generalization for object recognition with multi-task autoencoders
Muhammad Ghifary, W Bastiaan Kleijn, Mengjie Zhang, and David Balduzzi · 2015
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The Variational Fair Autoencoder
Christos Louizos, Kevin Swersky, Yujia Li, Max Welling, and Richard Zemel · 2015
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Multi-view domain generalization for visual recognition
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Robust domain generalisation by enforcing distribution invariance
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Domain-adversarial training of neural networks
Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, and Victor Lempitsky · 2016
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Muhammad Ghifary, David Balduzzi, W Bastiaan Kleijn, and Mengjie Zhang · 2016
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Li Niu, Wen Li, Dong Xu, and Jianfei Cai · 2016
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Domain generalization with adversarial feature learning
Haoliang Li, Sinno Jialin Pan, Shiqi Wang, and Alex C Kot · 2018
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Deep domain generalization via conditional invariant adversarial networks
Ya Li, Xinmei Tian, Mingming Gong, Yajing Liu, Tongliang Liu, Kun Zhang, and Dacheng Tao · 2018
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Learning adversarially fair and transferable representations
David Madras, Elliot Creager, Toniann Pitassi, and Richard Zemel · 2018
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Training replicable predictors in multiple studies
Prasad Patil and Giovanni Parmigiani · 2018
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Generalizing across domains via cross-gradient training
Shiv Shankar, Vihari Piratla, Soumen Chakrabarti, Siddhartha Chaudhuri, Preethi Jyothi, and Sunita Sarawagi · 2018
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Jonas Peters, Peter Bühlmann, and Nicolai Meinshausen · 2016
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Da Li, Yongxin Yang, Yi-Zhe Song, and Timothy M Hospedales · 2017
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Invariance, causality and robustness
Peter Bühlmann · 2018
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Generalizing to unseen domains via adversarial data augmentation
Riccardo Volpi, Hongseok Namkoong, Ozan Sener, John C Duchi, Vittorio Murino, and Silvio Savarese · 2018
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Invariant representations from adversarially censored autoencoders
Ye Wang, Toshiaki Koike-Akino, and Deniz Erdogmus · 2018
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Martin Arjovsky, Léon Bottou, Ishaan Gulrajani, and David Lopez-Paz · 2019
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Domain generalization using a mixture of multiple latent domains
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