Machine learning

Known as: Adaptive machine learning, Statistical learning, Learning algorithms 
Machine learning is the subfield of computer science that "gives computers the ability to learn without being explicitly programmed" (Arthur Samuel… (More)
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Topic mentions per year

Topic mentions per year

1936-2017
050001000019362016

Papers overview

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Highly Cited
2012
Highly Cited
2012
All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including… (More)
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Highly Cited
2011
Highly Cited
2011
Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale… (More)
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Highly Cited
2009
Highly Cited
2009
Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have… (More)
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Review
2007
Review
2007
Supervised machine learning is the search for algorithms that reason from externally supplied instances to produce general… (More)
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Highly Cited
2006
Highly Cited
2006
Goal A very fast, high quality corner detector. Contributions 1. The segment-test algorithm for detecting features. 2. Machine… (More)
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Review
2004
Review
2004
Cette thèse aborde de façon générale les algorithmes d'apprentissage, avec un intérêt tout particulier pour les grandes bases de… (More)
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Review
2003
Review
2003
This purpose of this introductory paper is threefold. First, it introduces the Monte Carlo method with emphasis on probabilistic… (More)
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Review
2002
Review
2002
Witten and Frank 's textbook was one of two books that 1 used for a data mining class in the Fall o f 2001. T h e book covers all… (More)
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Review
2002
Review
2002
The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last… (More)
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Highly Cited
1998
Highly Cited
1998
A central problem in machine learning is identifying a representative set of features from which to construct a classification… (More)
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