Sciweavers

1900 search results - page 2 / 380
» Gaussian Processes in Machine Learning
Sort
View
JMLR
2010
147views more  JMLR 2010»
14 years 7 months ago
Gaussian Processes for Machine Learning (GPML) Toolbox
The GPML toolbox provides a wide range of functionality for Gaussian process (GP) inference and prediction. GPs are specified by mean and covariance functions; we offer a library ...
Carl Edward Rasmussen, Hannes Nickisch
AC
2003
Springer
15 years 5 months ago
Gaussian Processes in Machine Learning
Carl Edward Rasmussen
DSMML
2004
Springer
15 years 5 months ago
Understanding Gaussian Process Regression Using the Equivalent Kernel
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...
Peter Sollich, Christopher K. I. Williams
112
Voted
ICML
2005
IEEE
16 years 1 months ago
Learning Gaussian processes from multiple tasks
We consider the problem of multi-task learning, that is, learning multiple related functions. Our approach is based on a hierarchical Bayesian framework, that exploits the equival...
Kai Yu, Volker Tresp, Anton Schwaighofer
ICML
2003
IEEE
16 years 1 months ago
Bayes Meets Bellman: The Gaussian Process Approach to Temporal Difference Learning
We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...
Yaakov Engel, Shie Mannor, Ron Meir