Leave-one-out support vector machines

IJCAI International Joint Conference on Artificial Intelligence

Volumn 2, Issue , 1999, Pages 727-731

  Weston, Jason ^a  

^a UNIVERSITY OF LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARK DATASETS; CONVEX OPTIMIZATION PROBLEMS; FREE PARAMETERS; LEAVE-ONE-OUT ERROR; LINEAR CLASSIFIERS; NEW APPROACHES; TRAINING ERRORS; UCI REPOSITORY;

ARTIFICIAL INTELLIGENCE; CONVEX OPTIMIZATION; LEARNING ALGORITHMS; PATTERN RECOGNITION;

SUPPORT VECTOR MACHINES;

EID: 84880679854     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (7)

1. Corinna Cortes and Vladimir Vapnik. Support Vector Networks. Machine Learning, 20:273-297, 1995.
2. Tommi S. Jaakkola and David Haussler. Probabilistic kernel regression models. In Proceedings of the 1999 Conference on AI and Statistics. Morgan Kaufmann, 1999.
3. E. Osuna and F. Girosi Reducing run-time complexity in SVMs. In Proceedings of the 14th Int'l Conf. on Pattern Recognition, Brisbane, Australia, 1998.
4. Gunnar Ratsch, T. Onoda, and Klaus-Robert Muller. Soft margins for adaboost. Technical report, Royal Holloway, University of London, 1998. TR-98-21.
5. Bernhard Scholkopf. Support Vector Learning. PhD thesis, Technische Universita Berlin, Berlin, Germany, 1997.
6. Vladimir Vapnik. The Nature of Statistical Learning Theory. Springer-Verlag, New York, 1995.
7. Vladimir Vapnik. Statistical Learning Theory. John Wiley and Sons, New York, 1998.