Unsupervised learning

Known as: Unsupervised approach, Unsupervised classification 
Unsupervised learning is the machine learning task of inferring a function to describe hidden structure from unlabeled data. Since the examples given… (More)
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Topic mentions per year

Topic mentions per year

1968-2017
050019682017

Papers overview

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Highly Cited
2015
Highly Cited
2015
We use multilayer Long Short Term Memory (LSTM) networks to learn representations of video sequences. Our model uses an encoder… (More)
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Highly Cited
2012
Highly Cited
2012
We consider the problem of building high-level, class-specific feature detectors from only unlabeled data. For example, is it… (More)
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Highly Cited
2010
Highly Cited
2010
Much recent research has been devoted to learning algorithms for deep architectures such as Deep Belief Networks and stacks of… (More)
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Highly Cited
2009
Highly Cited
2009
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling… (More)
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Highly Cited
2006
Highly Cited
2006
We present a novel unsupervised learning method for human action categories. A video sequence is represented as a collection of… (More)
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Highly Cited
2004
Highly Cited
2004
In this paper, we identify two issues involved in developing an automated feature subset selection algorithm for unlabeled data… (More)
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Highly Cited
2003
Highly Cited
2003
The problem of dimensionality reduction arises in many fields of information processing, including machine learning, data… (More)
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Highly Cited
2003
Highly Cited
2003
An unsupervised learning algorithm that can obtain a probabilistic model of an object composed of a collection of parts (a moving… (More)
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Highly Cited
2002
Highly Cited
2002
ÐThis paper proposes an unsupervised algorithm for learning a finite mixture model from multivariate data. The adjective… (More)
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Highly Cited
2001
Highly Cited
2001
This paper presents a novel statistical method for factor analysis of binary and count data which is closely related to a… (More)
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