A PAC-Bayes approach to the Set Covering Machine

Advances in Neural Information Processing Systems

Volumn , Issue , 2005, Pages 731-738

  Laviolette, François ^a   Marchand, Mario ^a   Shah, Mohak ^b  

^a UNIVERSITÉ LAVAL   (Canada)

^b UNIVERSITY OF OTTAWA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

NON-TRIVIAL; PAC-BAYES; SET COVERING MACHINES;

LEARNING ALGORITHMS;

RISK MANAGEMENT;

EID: 77952427773     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (7)

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2. John Langford. Tutorial on practical prediction theory for classification. Journal of Machine Learning Research, 6:273-306, 2005.
3. François Laviolette and Mario Marchand. PAC-Bayes risk bounds for sample-compressed Gibbs classifiers. Proceedings of the 22nth International Conference on Machine Learning (ICML 2005), pages 481-488, 2005.
4. th European Conference on Machine Learning (ECML 2005); Lecture Notes in Artificial Intelligence, 3720:206-217, 2005.
5. Mario Marchand and John Shawe-Taylor. The set covering machine. Journal of Machine Learning Reasearch, 3:723-746, 2002.
6. David McAllester. Some PAC-Bayesian theorems. Machine Learning, 37:355-363, 1999a.
7. David A. McAllester. Pac-bayesian model averaging. In COLT, pages 164-170, 1999b.