Roth V. (2006). Kernel fisher discriminants for outlier detection. Neural computation. 18 [PubMed]

See more from authors: Roth V

References and models cited by this paper

Duda RO, Hart PE, Stork DG. (2000). Pattern Classification (2nd edition).

Fox J. (1997). Applied regression, linear models, and related methods.

Huber P. (1981). Robust statistics.

Lepage G. (1980). Vegas: An adaptive multidimensional integration program Tech Rep CLNS-80-447.

Moody J. (1992). The effective number of parameters: An analysis of generalization and regularization in nonlinear learning systems Advances in neural information processing systems.

Roth V, Steinhage V. (2000). Nonlinear discriminant analysis using kernel functions Advances in neural information processing systems. 12

Scholkopf B, Muller KR, Mika S, Ratsch G, Weston J. (1999). Fisher discriminant analysis with kernels Neural networks for signal processing IX.

Scholkopf B, Smola AJ. (2001). Learning with kernels: Support vector machines, regularization, optimization, and beyond.

Schölkopf B et al. (1999). Input space versus feature space in kernel-based methods. IEEE transactions on neural networks. 10 [PubMed]

Shawe-taylor J, Williamson R, Scholkopf B, Smola A. (2000). SV estimation of a distributions support Advances in neural information processing systems. 12

Stuart A, Kendall M. (1977). The advanced theory of statistics. 1

Tax D, Duin R. (1999). Support vector data description Pattern Recognition Letters. 20

Tibshirani R, Hastie T, Buja A. (1995). Penalized discriminant analysis Annals Of Statistics. 23

van der Laan MJ, Dudoit S, Keles S. (2004). Asymptotic optimality of likelihood-based cross-validation. Statistical applications in genetics and molecular biology. 3 [PubMed]

References and models that cite this paper
This website requires cookies and limited processing of your personal data in order to function. By continuing to browse or otherwise use this site, you are agreeing to this use. See our Privacy policy and how to cite and terms of use.