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» Geodesic Gaussian kernels for value function approximation
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ESANN
2004
13 years 8 months ago
Sparse Bayesian kernel logistic regression
In this paper we present a simple hierarchical Bayesian treatment of the sparse kernel logistic regression (KLR) model based MacKay's evidence approximation. The model is re-p...
Gavin C. Cawley, Nicola L. C. Talbot
ILP
2003
Springer
14 years 19 days ago
Graph Kernels and Gaussian Processes for Relational Reinforcement Learning
RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...
Thomas Gärtner, Kurt Driessens, Jan Ramon
MOC
2000
88views more  MOC 2000»
13 years 7 months ago
On the error term of symmetric Gauss-Lobatto quadrature formulae for analytic functions
Gauss-Lobatto quadrature formulae associated with symmetric weight functions are considered. The kernel of the remainder term for classes of analytic functions is investigated on e...
David Hunter, Geno Nikolov
CSDA
2011
13 years 2 months ago
Approximate forward-backward algorithm for a switching linear Gaussian model
Motivated by the application of seismic inversion in the petroleum industry we consider a hidden Markov model with two hidden layers. The bottom layer is a Markov chain and given ...
Hugo Hammer, Håkon Tjelmeland
ADCM
2008
136views more  ADCM 2008»
13 years 7 months ago
Learning and approximation by Gaussians on Riemannian manifolds
Learning function relations or understanding structures of data lying in manifolds embedded in huge dimensional Euclidean spaces is an important topic in learning theory. In this ...
Gui-Bo Ye, Ding-Xuan Zhou