|
|
||||||||
Neural Computation, Vol 10, 1445-1454, Copyright © 1998 by The MIT Press
NOTES |
Tomaso Poggio and Federico Girosi
We derive a new general representation for a function as a linear combination of local correlation kernels at optimal sparse locations (and scales) and characterize its relation to principal component analysis, regularization, sparsity principles, and support vector machines.
This article has been cited by other articles:
![]() |
Z. Chen and S. Haykin On Different Facets of Regularization Theory Neural Comput., December 1, 2002; 14(12): 2791 - 2846. [Abstract] [Full Text] |
||||
![]() |
V. Tresp A Bayesian Committee Machine Neural Comput., November 1, 2000; 12(11): 2719 - 2741. [Abstract] [Full Text] |
||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| J COGNITIVE NEUROSCIENCE | NEURAL COMPUTATION | MIT PRESS JOURNALS |