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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Bayesian experimental designCold startEvolving intelligent systemList of datasets for machine learning research
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Machine learning

Papers overview

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Highly Cited
2010
Highly Cited
2010
Active Learning and Crowd-Sourcing for Machine Translation
In recent years, corpus based approaches to machine translation have become predominant, with Statistical Machine Translation… (More)
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Highly Cited
2006
Highly Cited
2006
Support vector machine active learning for music retrieval
Searching and organizing growing digital music collections requires a computational model of music similarity. This paper… (More)
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Highly Cited
2006
Highly Cited
2006
Batch mode active learning and its application to medical image classification
The goal of active learning is to select the most informative examples for manual labeling. Most of the previous studies in… (More)
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Highly Cited
2004
Highly Cited
2004
Active learning using pre-clustering
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
Online Choice of Active Learning Algorithms
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 Machine Active Learning with Applications to Text Classification
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
Toward Optimal Active Learning through Sampling Estimation of Error Reduction
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
Active Learning for Natural Language Parsing and Information Extraction
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
Employing EM and Pool-Based Active Learning for Text Classification
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
1994
Highly Cited
1994
Improving generalization with active learning
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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