112 search results - page 9 / 23 » Gaussian Processes for Machine Learning (GPML) Toolbox |
ECML
2007
Springer
14 years 1 months ago
2007
Springer
In this paper we address a method of source separation in the case where sources have certain temporal structures. The key contribution in this paper is to incorporate Gaussian pro...
ESSMAC
2003
Springer
14 years 25 days ago
2003
Springer
Gaussian Process prior models, as used in Bayesian non-parametric statistical models methodology are applied to implement a nonlinear adaptive control law. The expected value of a...
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Computer experiments often require dense sweeps over input parameters to obtain a qualitative understanding of their response. Such sweeps can be prohibitively expensive, and are ...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Many applications require optimizing an unknown, noisy function that is expensive to evaluate. We formalize this task as a multiarmed bandit problem, where the payoff function is ...
ESSMAC
2003
Springer
14 years 25 days ago
2003
Springer
Abstract. While there is strong motivation for using Gaussian Processes (GPs) due to their excellent performance in regression and classification problems, their computational com...