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Results: 1-25/435
Authors:
Cristianini, N
Campbell, C
Burges, C
Citation: N. Cristianini et al., Kernel methods: Current research and future directions, MACH LEARN, 46(1-3), 2002, pp. 5-9
Authors:
Williams, CKI
Citation: Cki. Williams, On a connection between kernel PCA and metric multidimensional scaling, MACH LEARN, 46(1-3), 2002, pp. 11-19
Authors:
Sollich, P
Citation: P. Sollich, Bayesian methods for support vector machines: Evidence and predictive class probabilities, MACH LEARN, 46(1-3), 2002, pp. 21-52
Authors:
Risau-Gusman, S
Gordon, MB
Citation: S. Risau-gusman et Mb. Gordon, Hierarchical learning in polynomial support vector machines, MACH LEARN, 46(1-3), 2002, pp. 53-70
Authors:
Gao, JB
Gunn, SR
Harris, CJ
Brown, M
Citation: Jb. Gao et al., A probabilistic framework for SVM regression and error bar estimation, MACH LEARN, 46(1-3), 2002, pp. 71-89
Authors:
Zhang, T
Citation: T. Zhang, On the dual formulation of regularized linear systems with convex risks, MACH LEARN, 46(1-3), 2002, pp. 91-129
Authors:
Chapelle, O
Vapnik, V
Bousquet, O
Mukherjee, S
Citation: O. Chapelle et al., Choosing multiple parameters for support vector machines, MACH LEARN, 46(1-3), 2002, pp. 131-159
Authors:
Decoste, D
Scholkopf, B
Citation: D. Decoste et B. Scholkopf, Training invariant support vector machines, MACH LEARN, 46(1-3), 2002, pp. 161-190
Authors:
Lin, Y
Lee, Y
Wahba, G
Citation: Y. Lin et al., Support vector machines for classification in nonstandard situations, MACH LEARN, 46(1-3), 2002, pp. 191-202
Authors:
Trafalis, TB
Malyscheff, AM
Citation: Tb. Trafalis et Am. Malyscheff, An analytic center machine, MACH LEARN, 46(1-3), 2002, pp. 203-223
Authors:
Demiriz, A
Bennett, KP
Shawe-Taylor, J
Citation: A. Demiriz et al., Linear programming boosting via column generation, MACH LEARN, 46(1-3), 2002, pp. 225-254
Authors:
Mangasarian, OL
Musicant, DR
Citation: Ol. Mangasarian et Dr. Musicant, Large scale kernel regression via linear programming, MACH LEARN, 46(1-3), 2002, pp. 255-269
Authors:
Flake, GW
Lawrence, S
Citation: Gw. Flake et S. Lawrence, Efficient SVM regression training with SMO, MACH LEARN, 46(1-3), 2002, pp. 271-290
Authors:
Hsu, CW
Lin, CJ
Citation: Cw. Hsu et Cj. Lin, A simple decomposition method for support vector machines, MACH LEARN, 46(1-3), 2002, pp. 291-314
Authors:
Laskov, P
Citation: P. Laskov, Feasible direction decomposition algorithms for training support vector machines, MACH LEARN, 46(1-3), 2002, pp. 315-349
Authors:
Keerthi, SS
Gilbert, EG
Citation: Ss. Keerthi et Eg. Gilbert, Convergence of a generalized SMO algorithm for SVM classifier design, MACH LEARN, 46(1-3), 2002, pp. 351-360
Authors:
Li, Y
Long, PM
Citation: Y. Li et Pm. Long, The relaxed online maximum margin algorithm, MACH LEARN, 46(1-3), 2002, pp. 361-387
Authors:
Guyon, I
Weston, J
Barnhill, S
Vapnik, V
Citation: I. Guyon et al., Gene selection for cancer classification using support vector machines, MACH LEARN, 46(1-3), 2002, pp. 389-422
Authors:
Leopold, E
Kindermann, J
Citation: E. Leopold et J. Kindermann, Text categorization with support vector machines. How to represent texts in input space ?, MACH LEARN, 46(1-3), 2002, pp. 423-444
Authors:
Morimoto, Y
Ishii, H
Morishita, S
Citation: Y. Morimoto et al., Efficient construction of regression trees with range and region splitting, MACH LEARN, 45(3), 2001, pp. 235-259
Authors:
Breiman, L
Citation: L. Breiman, Using iterated bagging to debias regressions, MACH LEARN, 45(3), 2001, pp. 261-277
Authors:
Thiesson, B
Meek, C
Heckerman, D
Citation: B. Thiesson et al., Accelerating EM for large databases, MACH LEARN, 45(3), 2001, pp. 279-299
Authors:
Kivinen, J
Warmuth, MK
Citation: J. Kivinen et Mk. Warmuth, Relative loss bounds for multidimensional regression problems, MACH LEARN, 45(3), 2001, pp. 301-329
Authors:
Mansour, Y
Schain, M
Citation: Y. Mansour et M. Schain, Learning with maximum-entropy distributions, MACH LEARN, 45(2), 2001, pp. 123-145
Authors:
Ramoni, M
Sebastiani, P
Citation: M. Ramoni et P. Sebastiani, Robust learning with missing data, MACH LEARN, 45(2), 2001, pp. 147-170