243 search results - page 5 / 49 » Non-linear regression models for Approximate Bayesian Comput... |
DIS
2006
Springer
13 years 11 months ago
2006
Springer
In supervised machine learning, variable ranking aims at sorting the input variables according to their relevance w.r.t. an output variable. In this paper, we propose a new relevan...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Traditional non-parametric statistical learning techniques are often computationally attractive, but lack the same generalization and model selection abilities as state-of-the-art...
BMCBI
2010
13 years 7 months ago
2010
Background: The estimation of demographic parameters from genetic data often requires the computation of likelihoods. However, the likelihood function is computationally intractab...
NIPS
2003
13 years 8 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...
ECAI
2008
Springer
13 years 9 months ago
2008
Springer
Abstract. Two approaches have been used to perform approximate inference in Bayesian networks for which exact inference is infeasible: employing an approximation algorithm, or appr...