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ICML
2009
IEEE
16 years 5 months ago
PAC-Bayesian learning of linear classifiers
We present a general PAC-Bayes theorem from which all known PAC-Bayes risk bounds are obtained as particular cases. We also propose different learning algorithms for finding linea...
Alexandre Lacasse, François Laviolette, Mar...
ECML
1998
Springer
15 years 8 months ago
First-Order Learning for Web Mining
We present compelling evidence that the World Wide Web is a domain in which applications can benefit from using first-order learning methods, since the graph structure inherent in ...
Mark Craven, Seán Slattery, Kamal Nigam
IJCV
2000
86views more  IJCV 2000»
15 years 4 months ago
Statistical Learning Theory: A Primer
In this paper we first overview the main concepts of Statistical Learning Theory, a framework in which learning from examples can be studied in a principled way. We then briefly di...
Theodoros Evgeniou, Massimiliano Pontil, Tomaso Po...
UAI
2000
15 years 5 months ago
Variational Relevance Vector Machines
The Support Vector Machine (SVM) of Vapnik [9] has become widely established as one of the leading approaches to pattern recognition and machine learning. It expresses predictions...
Christopher M. Bishop, Michael E. Tipping
CIKM
2009
Springer
15 years 11 months ago
Incremental query evaluation for support vector machines
Support vector machines (SVMs) have been widely used in multimedia retrieval to learn a concept in order to find the best matches. In such a SVM active learning environment, the ...
Danzhou Liu, Kien A. Hua