A formulation for minimax probability machine regression

Advances in Neural Information Processing Systems

Volumn , Issue , 2003, Pages

  Strohmann, Thomas ^a   Grudic, Gregory Z ^a  

^a UCB 450   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

MATHEMATICAL MODELS;

LOWER PROBABILITIES; MERCER KERNEL; MINIMAX PROBABILITY MACHINE; MINIMAX PROBABILITY MACHINE CLASSIFICATIONS; NONLINEAR REGRESSION MODELS; REGRESSION FUNCTION; REGRESSION MODEL; REGRESSION PROBLEM;

REGRESSION ANALYSIS;

EID: 84899018647     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (5)

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2. A. W. Marshall and I. Olkin. Multivariate chebyshev inequalities. Annals of Mathematical Statistics, 31(4): 1001-1014, 1960.
3. I. Popescu and D. Bertsimas. Optimal inequalities in probability theory: A convex optimization approach. Technical Report TM62, INSEAD, Dept. Math. O.R., Cambridge, Mass, 2001.
4. W. H. Press, B. P. Flannery, S. A. Teukolsky, and W. T. Vetterling. Numerical Recipes in C. Cambridge University Press, New York NY, 1988.
5. Bernhard Schölkopf, Peter L. Bartlett, Alex J. Smola, and Robert Williamson. Shrinking the tube: A new support vector regression algorithm. In D. A. Cohn M. S. Kearns, S. A. Solla, editor, Advances in Neural Information Processing Systems, Volume 11, Cambridge, MA, 1999. The MIT Press.