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Domain generalization (DG) aims to generalize a model trained on multiple source (i.e., training) domains to a distributionally different target (i.e., test) domain.
Neural network recognizer for hand-written zip code digits
John S. Denker, W. R. Gardner, Hans Peter Graf, Donnie Henderson, Richard E. Howard, Wayne E. Hubbard, Lawrence D. Jackel, Henry S. Baird, and Isabelle Guyon · 1988
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Gradient-based learning applied to document recognition
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner · 1998
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Visualizing data using t-sne
Laurens Van der Maaten and Geoffrey Hinton · 2008
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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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A theory of learning from different domains
Shai Ben-David, John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, and Jennifer Wortman Vaughan · 2010
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Co-regularization based semi-supervised domain adaptation
Hal Daumé III, Abhishek Kumar, and Avishek Saha · 2010
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A survey on transfer learning
Sinno Jialin Pan and Qiang Yang · 2010
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Reading digits in natural images with unsupervised feature learning
Yuval Netzer, Tao Wang, Adam Coates, Alessandro Bissacco, Bo Wu, and Andrew Y Ng · 2011
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton · 2012
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Unsupervised domain adaptation by domain invariant projection
Mahsa Baktashmotlagh, Mehrtash Tafazzoli Harandi, Brian C. Lovell, and Mathieu Salzmann · 2013
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Domain generalization via invariant feature representation
Krikamol Muandet, David Balduzzi, and Bernhard Schölkopf · 2013
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Unsupervised domain adaptation by backpropagation
Yaroslav Ganin and Victor S. Lempitsky · 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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Learning transferable features with deep adaptation networks
Mingsheng Long, Yue Cao, Jianmin Wang, and Michael I. 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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Domain-adversarial training of neural networks
Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, and Victor S. Lempitsky · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Wide residual networks
Sergey Zagoruyko and Nikos Komodakis · 2016
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A comprehensive survey on domain adaptation for visual applications
Gabriela Csurka · 2017
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Deeper, broader and artier domain generalization
Da Li, Yongxin Yang, Yi-Zhe Song, and Timothy M. Hospedales · 2017
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Deep transfer learning with joint adaptation networks
Mingsheng Long, Han Zhu, Jianmin Wang, and Michael I. Jordan · 2017
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Few-shot adversarial domain adaptation
Saeid Motiian, Quinn Jones, Seyed Mehdi Iranmanesh, and Gianfranco Doretto · 2017
Cited alongside, same era.
Unified deep supervised domain adaptation and generalization
Saeid Motiian, Marco Piccirilli, Donald A. Adjeroh, and Gianfranco Doretto · 2017
Cited alongside, same era.
Episodic training for domain generalization
Da Li, Jianshu Zhang, Yongxin Yang, Cong Liu, Yi-Zhe Song, and Timothy M. Hospedales · 2019
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Semi-supervised domain adaptation via minimax entropy
Kuniaki Saito, Donghyun Kim, Stan Sclaroff, Trevor Darrell, and Kate Saenko · 2019
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Learning robust global representations by penalizing local predictive power
Haohan Wang, Songwei Ge, Zachary C. Lipton, and Eric P. Xing · 2019
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Learning robust representations by projecting superficial statistics out
Haohan Wang, Zexue He, Zachary C. Lipton, and Eric P. Xing · 2019
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d-sne: Domain adaptation using stochastic neighborhood embedding
Xiang Xu, Xiong Zhou, Ragav Venkatesan, Gurumurthy Swaminathan, and Orchid Majumder · 2019
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Learning to balance specificity and invariance for in and out of domain generalization
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Metareg: Towards domain generalization using meta-regularization
Yogesh Balaji, Swami Sankaranarayanan, and Rama Chellappa · 2018
Cited alongside, same era.
Learning to generalize: Meta-learning for domain generalization
Da Li, Yongxin Yang, Yi-Zhe Song, and Timothy M. Hospedales · 2018
Cited alongside, same era.
Conditional adversarial domain adaptation
Mingsheng Long, Zhangjie Cao, Jianmin Wang, and Michael I. Jordan · 2018
Cited alongside, same era.
Best sources forward: Domain generalization through source-specific nets
Massimiliano Mancini, Samuel Rota Bulò, Barbara Caputo, and Elisa Ricci · 2018
Cited alongside, same era.
Generalizing across domains via cross-gradient training
Shiv Shankar, Vihari Piratla, Soumen Chakrabarti, Siddhartha Chaudhuri, Preethi Jyothi, and Sunita Sarawagi · 2018
Cited alongside, same era.
Representation learning with contrastive predictive coding
Aäron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
Cited alongside, same era.
Prithvijit Chattopadhyay, Yogesh Balaji, and Judy Hoffman · 2020
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CLUB: A contrastive log-ratio upper bound of mutual information
Pengyu Cheng, Weituo Hao, Shuyang Dai, Jiachang Liu, Zhe Gan, and Lawrence Carin · 2020
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Learning to learn with variational information bottleneck for domain generalization
Ying-Jun Du, Jun Xu, Huan Xiong, Qiang Qiu, Xiantong Zhen, Cees G. M. Snoek, and Ling Shao · 2020
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Self-challenging improves cross-domain generalization
Zeyi Huang, Haohan Wang, Eric P. Xing, and Dong Huang · 2020
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Supervised contrastive learning
Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, and Dilip Krishnan · 2020
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Progressive graph learning for open-set domain adaptation
Yadan Luo, Zijian Wang, Zi Huang, and Mahsa Baktashmotlagh · 2020
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Domain generalization using a mixture of multiple latent domains
Toshihiko Matsuura and Tatsuya Harada · 2020
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Learning to learn single domain generalization
Fengchun Qiao, Long Zhao, and Xi Peng · 2020
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Prototype-matching graph network for heterogeneous domain adaptation
Zijian Wang, Yadan Luo, Zi Huang, and Mahsa Baktashmotlagh · 2020
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Maximum-entropy adversarial data augmentation for improved generalization and robustness
Long Zhao, Ting Liu, Xi Peng, and Dimitris N. Metaxas · 2020
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Learning to generate novel domains for domain generalization
Kaiyang Zhou, Yongxin Yang, Timothy M. Hospedales, and Tao Xiang · 2020
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Robust and generalizable visual representation learning via random convolutions
Zhenlin Xu, Deyi Liu, Junlin Yang, Colin Raffel, and Marc Niethammer · 2021
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