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» Bayesian Parameter Estimation: A Monte Carlo Approach
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ICASSP
2010
IEEE
14 years 8 months ago
A partially collapsed Gibbs sampler for parameters with local constraints
We consider Bayesian detection/classification of discrete random parameters that are strongly dependent locally due to some deterministic local constraint. Based on the recently ...
Georg Kail, Jean-Yves Tourneret, Franz Hlawatsch, ...
ALT
2003
Springer
15 years 7 months ago
Kernel Trick Embedded Gaussian Mixture Model
In this paper, we present a kernel trick embedded Gaussian Mixture Model (GMM), called kernel GMM. The basic idea is to embed kernel trick into EM algorithm and deduce a parameter ...
Jingdong Wang, Jianguo Lee, Changshui Zhang
CSDA
2007
85views more  CSDA 2007»
14 years 10 months ago
Markov models for digraph panel data: Monte Carlo-based derivative estimation
A parametric, continuous-time Markov model for digraph panel data is considered. The parameter is estimated by the method of moments. A convenient method for estimating the varian...
Michael Schweinberger, Tom A. B. Snijders
JFR
2008
103views more  JFR 2008»
14 years 10 months ago
Monte Carlo localization in outdoor terrains using multilevel surface maps
We propose a novel combination of techniques for robustly estimating the position of a mobile robot in outdoor environments using range data. Our approach applies a particle filte...
Rainer Kümmerle, Rudolph Triebel, Patrick Pfa...
NECO
2002
145views more  NECO 2002»
14 years 9 months ago
Bayesian Model Assessment and Comparison Using Cross-Validation Predictive Densities
In this work, we discuss practical methods for the assessment, comparison, and selection of complex hierarchical Bayesian models. A natural way to assess the goodness of the model...
Aki Vehtari, Jouko Lampinen