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» Monte Carlo Localization with Mixture Proposal Distribution
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IVC
2008
141views more  IVC 2008»
13 years 7 months ago
Segmentation of color images via reversible jump MCMC sampling
Reversible jump Markov chain Monte Carlo (RJMCMC) is a recent method which makes it possible to construct reversible Markov chain samplers that jump between parameter subspaces of...
Zoltan Kato
KDD
2004
ACM
170views Data Mining» more  KDD 2004»
14 years 25 days ago
Estimating the size of the telephone universe: a Bayesian Mark-recapture approach
Mark-recapture models have for many years been used to estimate the unknown sizes of animal and bird populations. In this article we adapt a finite mixture mark-recapture model i...
David Poole
UAI
2000
13 years 8 months ago
Minimum Message Length Clustering Using Gibbs Sampling
The K-Means and EM algorithms are popular in clustering and mixture modeling due to their simplicity and ease of implementation. However, they have several significant limitations...
Ian Davidson
AAAI
2006
13 years 9 months ago
Probabilistic Self-Localization for Sensor Networks
This paper describes a technique for the probabilistic self-localization of a sensor network based on noisy inter-sensor range data. Our method is based on a number of parallel in...
Dimitri Marinakis, Gregory Dudek
ACG
2006
Springer
14 years 1 months ago
Solving Probabilistic Combinatorial Games
Probabilistic combinatorial games (PCG) are a model for Go-like games recently introduced by Ken Chen. They differ from normal combinatorial games since terminal position in each ...
Ling Zhao, Martin Müller 0003