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» On Bayesian model and variable selection using MCMC
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TSE
2002
105views more  TSE 2002»
14 years 9 months ago
Disaggregating and Calibrating the CASE Tool Variable in COCOMO II
CASE (Computer Aided Software Engineering) tools are believed to have played a critical role in improving software productivity and quality by assisting tasks in software developme...
Jongmoon Baik, Barry W. Boehm, Bert Steece
PE
2010
Springer
170views Optimization» more  PE 2010»
14 years 8 months ago
Approximating passage time distributions in queueing models by Bayesian expansion
We introduce Bayesian Expansion (BE), an approximate numerical technique for passage time distribution analysis in queueing networks. BE uses a class of Bayesian networks to appro...
Giuliano Casale
TIP
2008
163views more  TIP 2008»
14 years 9 months ago
Image Modeling and Denoising With Orientation-Adapted Gaussian Scale Mixtures
We develop a statistical model to describe the spatially varying behavior of local neighborhoods of coefficients in a multiscale image representation. Neighborhoods are modeled as ...
David K. Hammond, Eero P. Simoncelli
UAI
2004
14 years 11 months ago
Solving Factored MDPs with Continuous and Discrete Variables
Although many real-world stochastic planning problems are more naturally formulated by hybrid models with both discrete and continuous variables, current state-of-the-art methods ...
Carlos Guestrin, Milos Hauskrecht, Branislav Kveto...
JMLR
2010
218views more  JMLR 2010»
14 years 4 months ago
Simple Exponential Family PCA
Bayesian principal component analysis (BPCA), a probabilistic reformulation of PCA with Bayesian model selection, is a systematic approach to determining the number of essential p...
Jun Li, Dacheng Tao