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Classical machine learning assumes that the training and test sets come from the same distributions.
On information and sufficiency
Solomon Kullback and Richard A Leibler · 1951
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Harold Hotelling · 1992
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Vladimir Vapnik · 1992
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Multitask learning
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Avrim Blum and Tom Mitchell · 1998
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Improving predictive inference under covariate shift by weighting the log-likelihood function
Hidetoshi Shimodaira · 2000
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Learning and evaluating classifiers under sample selection bias
Bianca Zadrozny · 2004
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Semi-supervised learning literature survey
Xiaojin Jerry Zhu · 2005
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Model selection under covariate shift
Masashi Sugiyama and Klaus-Robert Müller · 2005
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Input-dependent estimation of generalization error under covariate shift
Masashi Sugiyama and Klaus-Robert Müller · 2005
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A kernel method for the two-sample-problem
Arthur Gretton, Karsten Borgwardt, Malte Rasch, Bernhard Schölkopf, and Alex J Smola · 2007
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Correcting sample selection bias by unlabeled data
Jiayuan Huang, Arthur Gretton, Karsten Borgwardt, Bernhard Schölkopf, and Alex J Smola · 2007
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Covariate shift adaptation by importance weighted cross validation
Masashi Sugiyama, Matthias Krauledat, and Klaus-Robert MÞller · 2007
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Analysis of representations for domain adaptation
Shai Ben-David, John Blitzer, Koby Crammer, and Fernando Pereira · 2007
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A survey of semi-supervised learning methods
Nitin Namdeo Pise and Parag Kulkarni · 2008
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Direct importance estimation with model selection and its application to covariate shift adaptation
Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashima, Paul V Buenau, and Motoaki Kawanabe · 2008
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Multi-view learning of acoustic features for speaker recognition
Karen Livescu and Mark Stoehr · 2009
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Covariate shift by kernel mean matching
Arthur Gretton, Alex Smola, Jiayuan Huang, Marcel Schmittfull, Karsten Borgwardt, and Bernhard Schölkopf · 2009
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A survey on transfer learning
SJ PAN · 2010
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Domain adaptation via transfer component analysis
Sinno Jialin Pan, Ivor W Tsang, James T Kwok, and Qiang Yang · 2010
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Binary coding of speech spectrograms using a deep auto-encoder
Li Deng, Michael L Seltzer, Dong Yu, Alex Acero, Abdel-rahman Mohamed, and Geoff Hinton · 2010
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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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Deconvolutional networks
Matthew D Zeiler, Dilip Krishnan, Graham W Taylor, and Rob Fergus · 2010
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Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Yoshua Bengio, Pierre-Antoine Manzagol, and Léon Bottou · 2010
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Collaborative topic modeling for recommending scientific articles
Chong Wang and David M Blei · 2011
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Domain adaptation for object recognition: An unsupervised approach
Raghuraman Gopalan, Ruonan Li, and Rama Chellappa · 2011
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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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Context-dependent pre-trained deep neural networks for large-vocabulary speech recognition
George E Dahl, Dong Yu, Li Deng, and Alex Acero · 2011
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Robust visual domain adaptation with low-rank reconstruction
I-Hong Jhuo, Dong Liu, DT Lee, and Shih-Fu Chang · 2012
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Nonparametric and semiparametric models
Wolfgang Karl Härdle, Marlene Müller, Stefan Sperlich, and Axel Werwatz · 2012
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Geodesic flow kernel for unsupervised domain adaptation
Boqing Gong, Yuan Shi, Fei Sha, and Kristen Grauman · 2012
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Stochastic gradient descent tricks
Léon Bottou · 2012
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Marginalized denoising autoencoders for domain adaptation
Minmin Chen, Zhixiang Xu, Kilian Weinberger, and Fei Sha · 2012
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Domain generalization via invariant feature representation
Krikamol Muandet, David Balduzzi, and Bernhard Schölkopf · 2013
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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Open set domain adaptation
Pau Panareda Busto and Juergen Gall · 2017
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Correlation alignment for unsupervised domain adaptation
Baochen Sun, Jiashi Feng, and Kate Saenko · 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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Unified deep supervised domain adaptation and generalization
Saeid Motiian, Marco Piccirilli, Donald A Adjeroh, and Gianfranco Doretto · 2017
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Unsupervised visual domain adaptation using subspace alignment
Basura Fernando, Amaury Habrard, Marc Sebban, and Tinne Tuytelaars · 2013
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Transfer feature learning with joint distribution adaptation
Mingsheng Long, Jianmin Wang, Guiguang Ding, Jiaguang Sun, and Philip S Yu · 2013
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Learning phrase representations using rnn encoder-decoder for statistical machine translation
Kyunghyun Cho, Bart Van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio · 2014
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Domain-adversarial neural networks
Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, and Mario Marchand · 2014
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Generalized transfer subspace learning through low-rank constraint
Ming Shao, Dmitry Kit, and Yun Fu · 2014
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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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Judy Hoffman, Eric Tzeng, Taesung Park, Jun-Yan Zhu, Phillip Isola, Kate Saenko, Alexei A Efros, and Trevor Darrell · 2017
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Adversarial discriminative domain adaptation
Eric Tzeng, Judy Hoffman, Kate Saenko, and Trevor Darrell · 2017
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Unsupervised pixel-level domain adaptation with generative adversarial networks
Konstantinos Bousmalis, Nathan Silberman, David Dohan, Dumitru Erhan, and Dilip Krishnan · 2017
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Learning from simulated and unsupervised images through adversarial training
Ashish Shrivastava, Tomas Pfister, Oncel Tuzel, Joshua Susskind, Wenda Wang, and Russell Webb · 2017
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Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros · 2017
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Region based image steganalysis using artificial bee colony
F Ghareh Mohammadi and Hedieh Sajedi · 2017
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Foundations of machine learning
Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar · 2018
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Open set domain adaptation by backpropagation
Kuniaki Saito, Shohei Yamamoto, Yoshitaka Ushiku, and Tatsuya Harada · 2018
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Partial transfer learning with selective adversarial networks
Zhangjie Cao, Mingsheng Long, Jianmin Wang, and Michael I Jordan · 2018
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Importance weighted adversarial nets for partial domain adaptation
Jing Zhang, Zewei Ding, Wanqing Li, and Philip Ogunbona · 2018
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Squeeze-and-excitation networks
Jie Hu, Li Shen, and Gang Sun · 2018
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Deep learning for sentiment analysis: A survey
Lei Zhang, Shuai Wang, and Bing Liu · 2018
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Dissection of deep learning with applications in image recognition
Soheyla Amirian, Zengyan Wang, Thiab R. Taha, and Hamid R. Arabnia · 2018
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Multi-adversarial domain adaptation
Zhongyi Pei, Zhangjie Cao, Mingsheng Long, and Jianmin Wang · 2018
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Deep learning at the edge
Sahar Voghoei, Navid Hashemi Tonekaboni, Jason G Wallace, and Hamid R Arabnia · 2018
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Universal domain adaptation
Kaichao You, Mingsheng Long, Zhangjie Cao, Jianmin Wang, and Michael I Jordan · 2019
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Contrastive adaptation network for unsupervised domain adaptation
Guoliang Kang, Lu Jiang, Yi Yang, and Alexander G Hauptmann · 2019
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Object detection with deep learning: A review
Zhong-Qiu Zhao, Peng Zheng, Shou-tao Xu, and Xindong Wu · 2019
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On parameter tuning in meta-learning for computer vision
Farid Ghareh Mohammadi, Hamid R Arabnia, and M Hadi Amini · 2019
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Deepmsrf: A novel deep multimodal speaker recognition framework with feature selection
Ehsan Asali, Farzan Shenavarmasouleh, Farid Ghareh Mohammadi, Prasanth Sengadu Suresh, and Hamid R Arabnia · 2020
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Personalized feedback emails: A case study on online introductory computer science courses
Sahar Voghoei, Navid Hashemi Tonekaboni, Delaram Yazdansepas, Saber Soleymani, Abolfazl Farahani, and Hamid R Arabnia · 2020
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Farzan Shenavarmasouleh and Hamid R Arabnia · 2020
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Video contents understanding using deep neural networks
Mohammadhossein Toutiaee, Abbas Keshavarzi, Abolfazl Farahani, and John A Miller · 2020
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