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Contrastive learning is a highly effective method for learning representations from unlabeled data.
An isoperimetric inequality on the discrete cube, and an elementary proof of the isoperimetric inequality in gauss space
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Spectral graph theory
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Improving predictive inference under covariate shift by weighting the log-likelihood function
Hidetoshi Shimodaira · 2000
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Improved baselines with momentum contrastive learning
Xinlei Chen, Haoqi Fan, Ross Girshick, and Kaiming He · 2003
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Big self-supervised models are strong semi-supervised learners
Ting Chen, Simon Kornblith, Kevin Swersky, Mohammad Norouzi, and Geoffrey Hinton · 2006
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Correcting sample selection bias by unlabeled data
Jiayuan Huang, Arthur Gretton, Karsten M Borgwardt, Bernhard Schölkopf, and Alex J Smola · 2006
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Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification
John Blitzer, Mark Dredze, and Fernando Pereira · 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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Covariate shift by kernel mean matching
Arthur Gretton, Alex Smola, Jiayuan Huang, Marcel Schmittfull, Karsten Borgwardt, and Bernhard Schölkopf · 2008
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Domain adaptation: Learning bounds and algorithms
Yishay Mansour, Mehryar Mohri, and Afshin Rostamizadeh · 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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Marginalized denoising autoencoders for domain adaptation
Minmin Chen, Zhixiang Xu, Kilian Q Weinberger, and Fei Sha · 2012
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Multiway spectral partitioning and higher-order cheeger inequalities
James R Lee, Shayan Oveis Gharan, and Luca Trevisan · 2014
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Approximation algorithm for sparsest k-partitioning
Anand Louis and Konstantin Makarychev · 2014
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Combining satellite imagery and machine learning to predict poverty
Neal Jean, Marshall Burke, Michael Xie, W. Matthew Davis, David B. Lobell, and Stefano Ermon · 2016
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Prototypical networks for few-shot learning
Jake Snell, Kevin Swersky, and Richard Zemel · 2017
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Neural structural correspondence learning for domain adaptation
Yftah Ziser and Roi Reichart · 2017
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Deep pivot-based modeling for cross-language cross-domain transfer with minimal guidance
Yftah Ziser and Roi Reichart · 2018
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A theoretical analysis of contrastive unsupervised representation learning
Sanjeev Arora, Hrishikesh Khandeparkar, Mikhail Khodak, Orestis Plevrakis, and Nikunj Saunshi · 2019
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Moment matching for multi-source domain adaptation
Xingchao Peng, Qinxun Bai, Xide Xia, Zijun Huang, Kate Saenko, and Bo Wang · 2019
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Bridging theory and algorithm for domain adaptation
Yuchen Zhang, Tianle Liu, Mingsheng Long, and Michael I Jordan · 2019
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Theoretical analysis of self-training with deep networks on unlabeled data, 2020
Colin Wei, Kendrick Shen, Yining Chen, and Tengyu Ma · 2020
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In-n-out: Pre-training and self-training using auxiliary information for out-of-distribution robustness
Sang Michael Xie, Ananya Kumar, Robbie Jones, Fereshte Khani, Tengyu Ma, and Percy Liang · 2020
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A theory of label propagation for subpopulation shift
Tianle Cai, Ruiqi Gao, Jason Lee, and Qi Lei · 2021
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Simcse: Simple contrastive learning of sentence embeddings
Tianyu Gao, Xingcheng Yao, and Danqi Chen · 2021
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Provable guarantees for self-supervised deep learning with spectral contrastive loss, 2021
Jeff Z. HaoChen, Colin Wei, Adrien Gaidon, and Tengyu Ma · 2021
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Han Zhao, Remi Tachet Des Combes, Kun Zhang, and Geoffrey Gordon · 2019
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Perl: Pivot-based domain adaptation for pre-trained deep contextualized embedding models
Eyal Ben-David, Carmel Rabinovitz, and Roi Reichart · 2020
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Unsupervised learning of visual features by contrasting cluster assignments
Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin · 2020
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Exploring simple siamese representation learning
Xinlei Chen and Kaiming He · 2020
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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Pretrained transformers improve out-of-distribution robustness
Dan Hendrycks, Xiaoyuan Liu, Eric Wallace, Adam Dziedzic, Rishabh Krishnan, and Dawn Song · 2020
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Understanding self-training for gradual domain adaptation
Ananya Kumar, Tengyu Ma, and Percy Liang · 2020
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Tacl: Improving bert pre-training with token-aware contrastive learning, 2021
Yixuan Su, Fangyu Liu, Zaiqiao Meng, Tian Lan, Lei Shu, Ehsan Shareghi, and Nigel Collier · 2021
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Contrastive domain adaptation
Mamatha Thota and Georgios Leontidis · 2021
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Contrastive learning, multi-view redundancy, and linear models
Christopher Tosh, Akshay Krishnamurthy, and Daniel Hsu · 2021
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Cross-domain contrastive learning for unsupervised domain adaptation
Rui Wang, Zuxuan Wu, Zejia Weng, Jingjing Chen, Guo-Jun Qi, and Yu-Gang Jiang · 2021
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Robust fine-tuning of zero-shot models
Mitchell Wortsman, Gabriel Ilharco, Mike Li, Jong Wook Kim, Hannaneh Hajishirzi, Ali Farhadi, Hongseok Namkoong, and Ludwig Schmidt · 2021
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Barlow twins: Self-supervised learning via redundancy reduction
Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, and Stéphane Deny · 2021
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A broad study of pre-training for domain generalization and adaptation
Donghyun Kim, Kaihong Wang, Stan Sclaroff, and Kate Saenko · 2022
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Fine-tuning can distort pretrained features and underperform out-of-distribution
Ananya Kumar, Aditi Raghunathan, Robbie Jones, Tengyu Ma, and Percy Liang · 2022
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Extending the wilds benchmark for unsupervised adaptation
Shiori Sagawa, Pang Wei Koh, Tony Lee, Irena Gao, Kendrick Shen Sang Michael Xie, Ananya Kumar, Weihua Hu, Michihiro Yasunaga, Sara Beery Henrik Marklund, Etienne David, Ian Stavness, Wei Guo, Jure Leskovec, Tatsunori Hashimoto Kate Saenko, Sergey Levine, Chelsea Finn, and Percy Liang · 2022
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Connect, not collapse: Explaining contrastive learning for unsupervised domain adaptation
Kendrick Shen, Robbie Jones, Ananya Kumar, Sang Michael Xie, Jeff Z. HaoChen, Tengyu Ma, and Percy Liang · 2022
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Mitchell Wortsman, Gabriel Ilharco, Samir Yitzhak Gadre, Rebecca Roelofs, Raphael Gontijo-Lopes, Ari S Morcos, Hongseok Namkoong, Ali Farhadi, Yair Carmon, Simon Kornblith, et al · 2022
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