Statistical Pattern Recognition Toolbox for Matlab User's guide

[1]  T. W. Anderson,et al.  Classification into two Multivariate Normal Distributions with Different Covariance Matrices , 1962 .

[2]  David G. Stork,et al.  Pattern Classification , 1973 .

[3]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[4]  Lawrence D. Jackel,et al.  Backpropagation Applied to Handwritten Zip Code Recognition , 1989, Neural Computation.

[5]  Heekuck Oh,et al.  Neural Networks for Pattern Recognition , 1993, Adv. Comput..

[6]  G. McLachlan,et al.  The EM algorithm and extensions , 1996 .

[7]  Bernhard Schölkopf,et al.  Fast Approximation of Support Vector Kernel Expansions, and an Interpretation of Clustering as Approximation in Feature Spaces , 1998, DAGM-Symposium.

[8]  Bernhard Schölkopf,et al.  Nonlinear Component Analysis as a Kernel Eigenvalue Problem , 1998, Neural Computation.

[9]  J. Platt Sequential Minimal Optimization : A Fast Algorithm for Training Support Vector Machines , 1998 .

[10]  Bernhard Schölkopf,et al.  Kernel Hebbian Algorithm for single-frame super-resolution , 1998 .

[11]  Gunnar Rätsch,et al.  Kernel PCA and De-Noising in Feature Spaces , 1998, NIPS.

[12]  Alexander J. Smola,et al.  Learning with kernels , 1998 .

[13]  B. Scholkopf,et al.  Fisher discriminant analysis with kernels , 1999, Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468).

[14]  B. Schölkopf,et al.  Advances in kernel methods: support vector learning , 1999 .

[15]  S. Sathiya Keerthi,et al.  A fast iterative nearest point algorithm for support vector machine classifier design , 2000, IEEE Trans. Neural Networks Learn. Syst..

[16]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[17]  G. Baudat,et al.  Generalized Discriminant Analysis Using a Kernel Approach , 2000, Neural Computation.

[18]  Robert P.W. Duin,et al.  PRTools3: A Matlab Toolbox for Pattern Recognition , 2000 .

[19]  P. Bartlett,et al.  Probabilities for SV Machines , 2000 .

[20]  Nello Cristianini,et al.  An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .

[21]  Shigeo Abe DrEng Pattern Classification , 2001, Springer London.

[22]  Ian T. Nabney,et al.  Netlab: Algorithms for Pattern Recognition , 2002 .

[23]  I. Jolliffe Principal Component Analysis , 2002 .

[24]  Chih-Jen Lin,et al.  A comparison of methods for multiclass support vector machines , 2002, IEEE Trans. Neural Networks.

[25]  Václav Hlavác,et al.  Ten Lectures on Statistical and Structural Pattern Recognition , 2002, Computational Imaging and Vision.

[26]  Václav Hlavác,et al.  Multi-class support vector machine , 2002, Object recognition supported by user interaction for service robots.

[27]  Václav Hlavác,et al.  Greedy Algorithm for a Training Set Reduction in the Kernel Methods , 2003, CAIP.

[28]  Václav Hlavác,et al.  An iterative algorithm learning the maximal margin classifier , 2003, Pattern Recognit..

[29]  Ivor W. Tsang,et al.  The pre-image problem in kernel methods , 2003, IEEE Transactions on Neural Networks.