Active learning (machine learning)

Known as: Pool-based active learning 
Active learning is a special case of semi-supervised machine learning in which a learning algorithm is able to interactively query the user (or some… (More)
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Papers overview

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Review
2017
Review
2017
Multi-Task Learning (MTL) is a learning paradigm in machine learning and its aim is to leverage useful information contained in… (More)
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Highly Cited
2008
Highly Cited
2008
We present an active learning scheme that exploits cluster structure in data. 
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Highly Cited
2004
Highly Cited
2004
The paper is concerned with two-class active learning. While the common approach for collecting data in active learning is to… (More)
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Highly Cited
2003
Highly Cited
2003
This paper is concerned with the question of how to online combine an ensemble of active learners so as to expedite the learning… (More)
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Highly Cited
2001
Highly Cited
2001
Support vector machines have met with significant success in numerous real-world learning tasks. However, like most machine… (More)
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Highly Cited
2001
Highly Cited
2001
This paper presents an active learning method that directly optimizes expected future error. This is in contrast to many other… (More)
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Highly Cited
1999
Highly Cited
1999
In natural language acquisition, it is difficult to gather the annotated data needed for supervised learning; however… (More)
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Highly Cited
1998
Highly Cited
1998
This paper shows how a text classifier’s need for labeled training documents can be reduced by taking advantage of a large pool… (More)
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Highly Cited
1997
Highly Cited
1997
In many real-world domains, supervised learning requires a large number of training examples. In this paper, we describe an… (More)
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Highly Cited
1994
Highly Cited
1994
Active learning differs from “learning from examples” in that the learning algorithm assumes at least some control over what part… (More)
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