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ICML
2009
IEEE
14 years 9 months ago
Approximate inference for planning in stochastic relational worlds
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
Tobias Lang, Marc Toussaint
FLAIRS
2009
13 years 6 months ago
A Comparative Study of Variable Elimination and Arc Reversal in Bayesian Network Inference
We compare two approaches to Bayesian network inference, called variable elimination (VE) and arc reversal (AR). It is established that VE never requires more space than AR, and n...
Cory J. Butz, Junying Chen, Ken Konkel, Pawan Ling...
CORR
2012
Springer
210views Education» more  CORR 2012»
12 years 4 months ago
Fast MCMC sampling for Markov jump processes and continuous time Bayesian networks
Markov jump processes and continuous time Bayesian networks are important classes of continuous time dynamical systems. In this paper, we tackle the problem of inferring unobserve...
Vinayak Rao, Yee Whye Teh
ISDA
2008
IEEE
14 years 3 months ago
Combining Clustering and Bayesian Network for Gene Network Inference
Gene network reconstruction is a multidisciplinary research area involving data mining, machine learning, statistics, ontologies and others. Reconstructed gene network allows us t...
Suhaila Zainudin, Safaai Deris
GLOBECOM
2010
IEEE
13 years 6 months ago
Cognitive Network Inference through Bayesian Network Analysis
Cognitive networking deals with applying cognition to the entire network protocol stack for achieving stack-wide as well as network-wide performance goals, unlike cognitive radios ...
Giorgio Quer, Hemanth Meenakshisundaram, Tamma Bhe...