582 search results - page 105 / 117 » Gaussian Processes in Reinforcement Learning |
ICIC
2005
Springer
14 years 3 months ago
2005
Springer
Rather than the difficulties of highly non-linear and non-Gaussian observation process and the state distribution in single target tracking, the presence of a large, varying number...
ESANN
2003
2003
Approximately unbiased estimation of conditional variance in heteroscedastic kernel ridge regression
13 years 11 months ago
In this paper we extend a form of kernel ridge regression for data characterised by a heteroscedastic noise process (introduced in Foxall et al. [1]) in order to provide approxima...
JMLR
2002
13 years 9 months ago
2002
A central problem in learning is selection of an appropriate model. This is typically done by estimating the unknown generalization errors of a set of models to be selected from a...
NIPS
1993
13 years 11 months ago
1993
Recent developments in the area of reinforcement learning have yielded a number of new algorithms for the prediction and control of Markovian environments. These algorithms,includ...
SODA
2012
ACM
12 years 2 days ago
2012
ACM
We consider the sparse Fourier transform problem: given a complex vector x of length n, and a parameter k, estimate the k largest (in magnitude) coefficients of the Fourier transf...