Monthly
288 pp. per issue
6 x 9, illustrated
ISSN
0899-7667
E-ISSN
1530-888X
2014 Impact factor:
2.21

Neural Computation

August 15, 1998, Vol. 10, No. 6, Pages 1445-1454
(doi: 10.1162/089976698300017250)
© 1998 Massachusetts Institute of Technology
A Sparse Representation for Function Approximation
Article PDF (243.52 KB)
Abstract

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.