1393 search results - page 111 / 279 » Machine Learning by Function Decomposition |
110
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COLT
2008
Springer
15 years 3 months ago
2008
Springer
We study distribution-dependent, data-dependent, learning in the limit with adversarial disturbance. We consider an optimization-based approach to learning binary classifiers from...
119
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ICML
2010
IEEE
14 years 11 months ago
2010
IEEE
Most learning to rank research has assumed that the utility of different documents is independent, which results in learned ranking functions that return redundant results. The fe...
111
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ICML
2009
IEEE
14 years 11 months ago
2009
IEEE
We address the problem of learning classifiers using several kernel functions. On the contrary to many contributions in the field of learning from different sources of information...
95
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NIPS
2007
15 years 3 months ago
2007
Incorporating invariances into a learning algorithm is a common problem in machine learning. We provide a convex formulation which can deal with arbitrary loss functions and arbit...
ICML
2005
IEEE
16 years 2 months ago
2005
IEEE
In the information regularization framework by Corduneanu and Jaakkola (2005), the distributions of labels are propagated on a hypergraph for semi-supervised learning. The learnin...