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CEC
2005
IEEE
16 years 5 days ago
Incorporating a Metropolis method in a distribution estimation using Markov random field algorithm
Abstract- Markov Random Field (MRF) modelling techniques have been recently proposed as a novel approach to probabilistic modelling for Estimation of Distribution Algorithms (EDAs)...
Siddhartha Shakya, John A. W. McCall, Deryck F. Br...
ECML
2006
Springer
15 years 10 months ago
Combinatorial Markov Random Fields
Abstract. A combinatorial random variable is a discrete random variable defined over a combinatorial set (e.g., a power set of a given set). In this paper we introduce combinatoria...
Ron Bekkerman, Mehran Sahami, Erik G. Learned-Mill...
IJCAI
2007
15 years 8 months ago
Using Linear Programming for Bayesian Exploration in Markov Decision Processes
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
Pablo Samuel Castro, Doina Precup
NIPS
2008
15 years 8 months ago
Partially Observed Maximum Entropy Discrimination Markov Networks
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
Jun Zhu, Eric P. Xing, Bo Zhang
WSC
1997
15 years 8 months ago
A New Variance-Reduction Technique for Regenerative Simulations of Markov Chains
We propose a new estimator for some performance measures obtained from a regenerative simulation of a discrete-time Markov chain. Our new estimator is based on the idea of generat...
James M. Calvin, Marvin K. Nakayama