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ICRA
2005
IEEE
150views Robotics» more  ICRA 2005»
14 years 2 months ago
Learning Sensor Network Topology through Monte Carlo Expectation Maximization
— We consider the problem of inferring sensor positions and a topological (i.e. qualitative) map of an environment given a set of cameras with non-overlapping fields of view. In...
Dimitri Marinakis, Gregory Dudek, David J. Fleet
ICARCV
2008
IEEE
170views Robotics» more  ICARCV 2008»
14 years 3 months ago
A fast Monte Carlo algorithm for collision probability estimation
—In order to navigate safely, it is important to detect and to react to a potentially dangerous situation. Such a situation can be underlined by a judicious use of the locations ...
Alain Lambert, Dominique Gruyer, Guillaume Saint-P...
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...
ICPR
2002
IEEE
14 years 10 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...
ISVC
2009
Springer
14 years 3 months ago
Multi-target and Multi-camera Object Detection with Monte-Carlo Sampling
In this paper, we propose a general-purpose methodology for detecting multiple objects with known visual models from multiple views. The proposed method is based Monte-Carlo sampli...
Giorgio Panin, Sebastian Klose, Alois Knoll