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» Introduction to Monte Carlo simulation
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AAAI
2004
14 years 11 months ago
Bayesian Inference on Principal Component Analysis Using Reversible Jump Markov Chain Monte Carlo
Based on the probabilistic reformulation of principal component analysis (PCA), we consider the problem of determining the number of principal components as a model selection prob...
Zhihua Zhang, Kap Luk Chan, James T. Kwok, Dit-Yan...
FLAIRS
2001
14 years 11 months ago
A Practical Markov Chain Monte Carlo Approach to Decision Problems
Decisionand optimizationproblemsinvolvinggraphsarise in manyareas of artificial intelligence, including probabilistic networks, robot navigation, and network design. Manysuch prob...
Timothy Huang, Yuriy Nevmyvaka
UAI
2001
14 years 11 months ago
Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk
We present an iterative Markov chain Monte Carlo algorithm for computing reference priors and minimax risk for general parametric families. Our approach uses MCMC techniques based...
John D. Lafferty, Larry A. Wasserman
RC
2007
78views more  RC 2007»
14 years 9 months ago
Monte-Carlo-Type Techniques for Processing Interval Uncertainty, and Their Potential Engineering Applications
Abstract. In engineering applications, we need to make decisions under uncertainty. Traditionally, in engineering, statistical methods are used, methods assuming that we know the p...
Vladik Kreinovich, Jan Beck, Carlos Ferregut, Arac...
ICASSP
2011
IEEE
14 years 1 months ago
Sequential Monte Carlo Radio-Frequency tomographic tracking
Radio Frequency (RF) tomographic tracking is the process of tracking moving targets by analyzing changes of attenuation in wireless transmissions. This paper presents a novel sequ...
Yunpeng Li, Xi Chen, Mark Coates, Bo Yang