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» Kolmogorov-Loveland Randomness and Stochasticity
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NIPS
2003
13 years 9 months ago
Approximate Policy Iteration with a Policy Language Bias
We study an approach to policy selection for large relational Markov Decision Processes (MDPs). We consider a variant of approximate policy iteration (API) that replaces the usual...
Alan Fern, Sung Wook Yoon, Robert Givan
ECAI
2010
Springer
13 years 8 months ago
Bayesian Monte Carlo for the Global Optimization of Expensive Functions
In the last decades enormous advances have been made possible for modelling complex (physical) systems by mathematical equations and computer algorithms. To deal with very long run...
Perry Groot, Adriana Birlutiu, Tom Heskes
ICML
2010
IEEE
13 years 8 months ago
Particle Filtered MCMC-MLE with Connections to Contrastive Divergence
Learning undirected graphical models such as Markov random fields is an important machine learning task with applications in many domains. Since it is usually intractable to learn...
Arthur Asuncion, Qiang Liu, Alexander T. Ihler, Pa...
CSDA
2010
122views more  CSDA 2010»
13 years 7 months ago
Nonparametric density estimation for positive time series
The Gaussian kernel density estimator is known to have substantial problems for bounded random variables with high density at the boundaries. For i.i.d. data several solutions hav...
Taoufik Bouezmarni, Jeroen V. K. Rombouts
ENTCS
2008
120views more  ENTCS 2008»
13 years 7 months ago
Specifying and Executing Reactive Scenarios With Lutin
This paper presents the language Lutin and its operational semantics. This language specifically targets the domain of reactive systems, where an execution is a (virtually) infini...
Pascal Raymond, Yvan Roux, Erwan Jahier