Co-training

Co-training is a machine learning algorithm used when there are only small amounts of labeled data and large amounts of unlabeled data. One of its… (More)
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Topic mentions per year

1999-2017
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Papers overview

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Highly Cited
2011
Highly Cited
2011
Domain adaptation algorithms seek to generalize a model trained in a source domain to a new target domain. In many practical… (More)
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Highly Cited
2011
Highly Cited
2011
We propose a spectral clustering algorithm for the multi-view setting where we have access to multiple views of the data, each of… (More)
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2011
2011
Recently, Semi-Supervised learning algorithms such as co-training are used in many domains. In co-training, two classifiers based… (More)
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2008
2008
Semi-supervised learning has received much attention recently. Co-training is a kind of semi-supervised learning method which… (More)
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Highly Cited
2007
Highly Cited
2007
Co-training is a semi-supervised learning paradigm which trains two learners respectively from two different views and lets the… (More)
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Highly Cited
2004
Highly Cited
2004
This paper investigates the application of cotraining and self-training to word sense disambiguation. Optimal and empirical… (More)
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Highly Cited
2004
Highly Cited
2004
Co-training is a method for combining labeled and unlabeled data when examples can be thought of as containing two distinct sets… (More)
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2003
2003
Corrected co-training (Pierce & Cardie, 2001) and the closely related co-testing (Muslea et al., 2000) are active learning… (More)
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Highly Cited
2001
Highly Cited
2001
The rule-based bootstrapping introduced by Yarowsky, and its cotraining variant by Blum and Mitchell, have met with considerable… (More)
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Highly Cited
2000
Highly Cited
2000
Recently there has been signi cant interest in supervised learning algorithms that combine labeled and unlabeled data for text… (More)
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