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» Speeeding Up Markov Chain Monte Carlo Algorithms
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CVPR
2004
IEEE
15 years 4 months ago
Modeling Complex Motion by Tracking and Editing Hidden Markov Graphs
In this paper, we propose a generative model for representing complex motion, such as wavy river, dancing fire and dangling cloth. Our generative method consists of four component...
Yizhou Wang, Song Chun Zhu
120
Voted
ICML
2009
IEEE
16 years 1 months ago
Archipelago: nonparametric Bayesian semi-supervised learning
Semi-supervised learning (SSL), is classification where additional unlabeled data can be used to improve accuracy. Generative approaches are appealing in this situation, as a mode...
Ryan Prescott Adams, Zoubin Ghahramani
123
Voted
DSN
2007
IEEE
15 years 7 months ago
Variational Bayesian Approach for Interval Estimation of NHPP-Based Software Reliability Models
In this paper, we present a variational Bayesian (VB) approach to computing the interval estimates for nonhomogeneous Poisson process (NHPP) software reliability models. This appr...
Hiroyuki Okamura, Michael Grottke, Tadashi Dohi, K...
ICIP
2010
IEEE
14 years 10 months ago
Instrument parameter estimation in bayesian convex deconvolution
This paper proposes a Bayesian approach for estimation of instrument parameter in convex image deconvolution. The parameters of the instrument response (PSF) are jointly estimated...
François Orieux, Thomas Rodet, Jean-Fran&cc...
120
Voted
UAI
1996
15 years 2 months ago
Bayesian Learning of Loglinear Models for Neural Connectivity
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Kathryn B. Laskey, Laura Martignon