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Self-training is one of the earliest and simplest semi-supervised methods.
Probability of error of some adaptive pattern-recognition machines
H Scudder · 1965
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Unsupervised word sense disambiguation rivaling supervised methods
David Yarowsky · 1995
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Combining labeled and unlabeled data with co-training
Avrim Blum and Tom Mitchell · 1998
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BLEU: a method for automatic evaluation of machine translation
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Democratic co-learning
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Semi-supervised classification by low density separation
Olivier Chapelle and Alexander Zien · 2005
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Semi-supervised learning by entropy minimization
Yves Grandvalet and Yoshua Bengio · 2005
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Tri-training: Exploiting unlabeled data using three classifiers
Zhi-Hua Zhou and Ming Li · 2005
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Effective self-training for parsing
David McClosky, Eugene Charniak, and Mark Johnson · 2006
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Using monolingual source-language data to improve mt performance
Nicola Ueffing · 2006
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Self-training for enhancement and domain adaptation of statistical parsers trained on small datasets
Roi Reichart and Ari Rappoport · 2007
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Semi-supervised learning (chapelle, o. et al., eds.; 2006)[book reviews]
Olivier Chapelle, Bernhard Scholkopf, and Alexander Zien · 2009
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Self-training pcfg grammars with latent annotations across languages
Zhongqiang Huang and Mary Harper · 2009
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Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E Hinton, Nitish Srivastava, Alex Krizhevsky, Ilya Sutskever, and Ruslan R Salakhutdinov · 2012
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Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks
Dong-Hyun Lee · 2013
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Semi-supervised learning with deep generative models
Durk P Kingma, Shakir Mohamed, Danilo Jimenez Rezende, and Max Welling · 2014
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Temporal ensembling for semi-supervised learning
Samuli Laine and Timo Aila · 2017
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Adversarial training methods for semi-supervised text classification
Takeru Miyato, Andrew M Dai, and Ian Goodfellow · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Semi-supervised sequence modeling with cross-view training
Kevin Clark, Minh-Thang Luong, Christopher D Manning, and Quoc V Le · 2018
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Understanding back-translation at scale
Sergey Edunov, Myle Ott, Michael Auli, and David Grangier · 2018
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Phrase-based & neural unsupervised machine translation
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The FLoRes evaluation datasets for low-resource machine translation: Nepali-english and sinhala-english
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fairseq: A fast, extensible toolkit for sequence modeling
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Unsupervised data augmentation
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