33 search results - page 1 / 7 » Sequential Bayesian Kernel Regression |
94
Voted
NIPS
2003
14 years 11 months ago
2003
We propose a method for sequential Bayesian kernel regression. As is the case for the popular Relevance Vector Machine (RVM) [10, 11], the method automatically identifies the num...
ESANN
2004
14 years 11 months ago
2004
In this paper we present a simple hierarchical Bayesian treatment of the sparse kernel logistic regression (KLR) model based MacKay's evidence approximation. The model is re-p...
NIPS
2008
14 years 11 months ago
2008
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
ICCV
2009
IEEE
14 years 7 months ago
2009
IEEE
Poisson regression models the noisy output of a counting function as a Poisson random variable, with a log-mean parameter that is a linear function of the input vector. In this wo...
94
Voted
NIPS
2004
14 years 11 months ago
2004
We present a novel method for learning with Gaussian process regression in a hierarchical Bayesian framework. In a first step, kernel matrices on a fixed set of input points are l...