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ADCM
2006
74views more  ADCM 2006»
13 years 6 months ago
Linearly constrained reconstruction of functions by kernels with applications to machine learning
This paper investigates the approximation of multivariate functions from data via linear combinations of translates of a positive definite kernel from a reproducing kernel Hilbert...
Robert Schaback, J. Werner
ICASSP
2011
IEEE
12 years 10 months ago
Theoretical analyses on a class of nested RKHS's
One of central topics of kernel machines in the field of machine learning is a model selection, especially a selection of a kernel or its parameters. In our previous work, we dis...
Akira Tanaka, Hideyuki Imai, Mineichi Kudo, Masaak...
NIPS
2004
13 years 7 months ago
Kernels for Multi--task Learning
This paper provides a foundation for multi
Charles A. Micchelli, Massimiliano Pontil
DIS
2007
Springer
14 years 13 days ago
A Hilbert Space Embedding for Distributions
We describe a technique for comparing distributions without the need for density estimation as an intermediate step. Our approach relies on mapping the distributions into a reprodu...
Alexander J. Smola, Arthur Gretton, Le Song, Bernh...
FOCM
2006
97views more  FOCM 2006»
13 years 6 months ago
Learning Rates of Least-Square Regularized Regression
This paper considers the regularized learning algorithm associated with the leastsquare loss and reproducing kernel Hilbert spaces. The target is the error analysis for the regres...
Qiang Wu, Yiming Ying, Ding-Xuan Zhou