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NN
2006
Springer
127views Neural Networks» more  NN 2006»
15 years 7 months ago
The asymptotic equipartition property in reinforcement learning and its relation to return maximization
We discuss an important property called the asymptotic equipartition property on empirical sequences in reinforcement learning. This states that the typical set of empirical seque...
Kazunori Iwata, Kazushi Ikeda, Hideaki Sakai
JUCS
2002
90views more  JUCS 2002»
15 years 6 months ago
How Large is the Set of Disjunctive Sequences?
: We consider disjunctive sequences, that is, infinite sequences (-words) having all finite words as infixes. It is shown that the set of all disjunctive sequences can be described...
Ludwig Staiger
CGF
2008
141views more  CGF 2008»
15 years 6 months ago
Accelerating Ray Tracing using Constrained Tetrahedralizations
In this paper we introduce the constrained tetrahedralization as a new acceleration structure for ray tracing. A constrained tetrahedralization of a scene is a tetrahedralization ...
Ares Lagae, Philip Dutré
PKDD
2010
Springer
179views Data Mining» more  PKDD 2010»
15 years 5 months ago
Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-Like Exploration
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
Tobias Jung, Peter Stone
CVPR
2008
IEEE
16 years 9 months ago
Conditional density learning via regression with application to deformable shape segmentation
Many vision problems can be cast as optimizing the conditional probability density function p(C|I) where I is an image and C is a vector of model parameters describing the image. ...
Jingdan Zhang, Shaohua Kevin Zhou, Dorin Comaniciu...