267 search results - page 5 / 54 » Ridgelet kernel regression |
JMLR
2011
13 years 2 months ago
2011
We propose a fully Bayesian methodology for generalized kernel mixed models (GKMMs), which are extensions of generalized linear mixed models in the feature space induced by a repr...
DSMML
2004
Springer
14 years 1 months ago
2004
Springer
The equivalent kernel [1] is a way of understanding how Gaussian process regression works for large sample sizes based on a continuum limit. In this paper we show how to approximat...
ICPR
2010
IEEE
13 years 11 months ago
2010
IEEE
Multiple kernel learning (MKL) uses a weighted combination of kernels where the weight of each kernel is optimized during training. However, MKL assigns the same weight to a kerne...
ECML
2007
Springer
14 years 2 months ago
2007
Springer
Abstract. Consider the online regression problem where the dependence of the outcome yt on the signal xt changes with time. Standard regression techniques, like Ridge Regression, d...
JMLR
2010
13 years 2 months ago
2010
Universal kernels have been shown to play an important role in the achievability of the Bayes risk by many kernel-based algorithms that include binary classification, regression, ...