What's in a Domain? Learning Domain-Robust Text Representations using Adversarial Training

N-gram-based text categorization

William B Cavnar and John M Trenkle. 1994 · 1994

Earlier work this paper cites.

Europarl: A parallel corpus for statistical machine translation

Philipp Koehn. 2005 · 2005

Earlier work this paper cites.

Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification

John Blitzer, Mark Dredze, and Fernando Pereira. 2007 · 2007

Earlier work this paper cites.

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Hal Daumé III. 2007 · 2007

Earlier work this paper cites.

News from OPUS – a collection of multilingual parallel corpora with tools and interfaces

Jörg Tiedemann. 2009 · 2009

Earlier work this paper cites.

Language identification: The long and the short of the matter

Timothy Baldwin and Marco Lui. 2010 · 2010

Earlier work this paper cites.

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Marco Lui and Timothy Baldwin. 2011 · 2011

Earlier work this paper cites.

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Erik Tromp and Mykola Pechenizkiy. 2011 · 2011

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Mahesh Joshi, Mark Dredze, William W. Cohen, and Carolyn Penstein Rosé. 2012 · 2012

Cited alongside, same era.

langid.py: An off-the-shelf language identification tool

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Cited alongside, same era.

Microblog language identification: Overcoming the limitations of short, unedited and idiomatic text

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Cited alongside, same era.

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Cited alongside, same era.

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Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, and Yoshua Bengio. 2014 · 2014

Accurate language identification of Twitter messages

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Later among the works it cites.

Non-linear text regression with a deep convolutional neural network

Zsolt Bitvai and Trevor Cohn. 2015 · 2015

Later among the works it cites.

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Yaroslav Ganin and Victor Lempitsky. 2015 · 2015

Later among the works it cites.

Adam: A method for stochastic optimization

Diederik P. Kingma and Jimmy Ba. 2015 · 2015

Later among the works it cites.

Domain-adversarial training of neural networks

Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, and Victor Lempitsky. 2016 · 2016

Later among the works it cites.

Frustratingly easy neural domain adaptation

Young-Bum Kim, Karl Stratos, and Ruhi Sarikaya. 2016 · 2016

Later among the works it cites.