203 search results - page 2 / 41 » Hierarchical Gaussian Process Regression |
76
Voted
ICML
2006
IEEE
15 years 11 months ago
2006
IEEE
Ordinal regression has become an effective way of learning user preferences, but most of research only focuses on single regression problem. In this paper we introduce collaborati...
124
click to vote
BMCBI
2007
14 years 10 months ago
2007
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
84
Voted
ICML
2005
IEEE
15 years 11 months ago
2005
IEEE
This paper presents an algorithm to estimate simultaneously both mean and variance of a non parametric regression problem. The key point is that we are able to estimate variance l...
ICASSP
2010
IEEE
14 years 10 months ago
2010
IEEE
We investigate the use of hierarchical Gaussian shortlists to speed up Gaussian likelihood computation. This approach is a combination of hierarchical Gaussian selection and stand...
78
Voted
NIPS
2004
14 years 11 months ago
2004
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 (1) how to appro...