Robust novelty detection with single-class MPM

Advances in Neural Information Processing Systems

Volumn , Issue , 2003, Pages

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

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COVARIANCE MATRIX; SET THEORY;

CONVEX SET; DATA POINTS; DATA SET; DISTRIBUTION-FREE; INPUT SPACE; MINIMAX PROBABILITY MACHINE; NOVELTY DETECTION; ROBUST APPROACHES;

PROBABILITY DISTRIBUTIONS;

EID: 84899015927     PISSN: 10495258     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. I. Jordan. A robust minimax approach to classification. Journal of Machine Learning Research, 3:555-582, 2002.
4. B. Schölkopf and A. Smola. Learning with Kernels. MIT Press, Cambridge, MA, 2001.