Robust Novelty Detection with Single-Class MPM

NIPS 2002: Proceedings of the 15th International Conference on Neural Information Processing Systems

Volumn , Issue , 2002, Pages 905-912

  Lanckriet, Gert R G ^a   Ghaoui, Laurent E I ^a   Jordan, Michael I ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PROBABILITY DISTRIBUTIONS; SET THEORY;

CONVEX SET; COVARIANCE MATRICES; DATA SET; DATAPOINTS; DISTRIBUTION-FREE; INPUT SPACE; MACHINE SETTINGS; MINIMAX PROBABILITY MACHINE; NOVELTY DETECTION; ROBUST APPROACHES;

COVARIANCE MATRIX;

EID: 85156229065     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (4)

1. S. Ben-David and M. Lindenbaum. Learning distributions by their density levels: A paradigm for learning without a teacher. Journal of Computer and System Sciences, 55: 171-182, 1997.
2. L. Breiman. Arcing classifiers. Technical Report Technical Report 460, Statistics Department, University of California, 1997.
3. G. Lanckriet, L. El Ghaoui, C. Bhattacharyya, and M. 1. Jordan. A robust minimax approach to classification. Journal of Machine Learning Research, 3:555-582, 2002.
4. B. SchOlkopf and A. Smola. Learning with Kernels. MIT Press, Cambridge, MA, 2001.