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» Stochastic complexity in learning
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NIPS
2004
15 years 7 months ago
Computing regularization paths for learning multiple kernels
The problem of learning a sparse conic combination of kernel functions or kernel matrices for classification or regression can be achieved via the regularization by a block 1-norm...
Francis R. Bach, Romain Thibaux, Michael I. Jordan
CORR
2010
Springer
81views Education» more  CORR 2010»
15 years 6 months ago
Using machine learning to make constraint solver implementation decisions
Programs to solve so-called constraint problems are complex pieces of software which require many design decisions to be made more or less arbitrarily by the implementer. These dec...
Lars Kotthoff, Ian P. Gent, Ian Miguel
ECAI
2010
Springer
15 years 4 months ago
Learning conditionally lexicographic preference relations
Abstract. We consider the problem of learning a user's ordinal preferences on a multiattribute domain, assuming that her preferences are lexicographic. We introduce a general ...
Richard Booth, Yann Chevaleyre, Jérôm...
NAACL
2010
15 years 3 months ago
Painless Unsupervised Learning with Features
We show how features can easily be added to standard generative models for unsupervised learning, without requiring complex new training methods. In particular, each component mul...
Taylor Berg-Kirkpatrick, Alexandre Bouchard-C&ocir...
ICMCS
2009
IEEE
132views Multimedia» more  ICMCS 2009»
15 years 3 months ago
Video face recognition with graph-based semi-supervised learning
We consider the problem of classification of multiple observations of the same object, possibly under different transformations. We view this problem as a special case of semi-sup...
Effrosini Kokiopoulou, Pascal Frossard