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JMLR
2010
139views more  JMLR 2010»
13 years 3 months ago
Tempered Markov Chain Monte Carlo for training of Restricted Boltzmann Machines
Alternating Gibbs sampling is the most common scheme used for sampling from Restricted Boltzmann Machines (RBM), a crucial component in deep architectures such as Deep Belief Netw...
Guillaume Desjardins, Aaron C. Courville, Yoshua B...
SIGSOFT
2009
ACM
14 years 9 months ago
Reo2MC: a tool chain for performance analysis of coordination models
In this paper, we present Reo2MC, a tool chain for the performance evaluation of coordination models. Given a coordination model represented by a stochastic Reo connector, Reo2MC ...
Farhad Arbab, Sun Meng, Young-Joo Moon, Marta Z. K...
ICPR
2002
IEEE
14 years 9 months ago
Learning Bayesian Network Classifiers for Credit Scoring Using Markov Chain Monte Carlo Search
In this paper, we will evaluate the power and usefulness of Bayesian network classifiers for credit scoring. Various types of Bayesian network classifiers will be evaluated and co...
Bart Baesens, Michael Egmont-Petersen, Robert Cast...
AUTOMATICA
2005
117views more  AUTOMATICA 2005»
13 years 8 months ago
Dwell-time controllers for stochastic systems with switching Markov chain
We study the problem of feedback stabilization of a family of nonlinear stochastic systems with switching mechanism modeled by a Markov chain. We introduce a novel notion of stabi...
Stefano Battilotti, A. De Santis
ICML
2004
IEEE
14 years 9 months ago
Approximate inference by Markov chains on union spaces
A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distr...
Max Welling, Michal Rosen-Zvi, Yee Whye Teh