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ICLP
2010
Springer
13 years 11 months ago
Improving the Efficiency of Gibbs Sampling for Probabilistic Logical Models by Means of Program Specialization
Abstract. There is currently a large interest in probabilistic logical models. A popular algorithm for approximate probabilistic inference with such models is Gibbs sampling. From ...
Daan Fierens
CLOR
2006
13 years 11 months ago
Sequential Learning of Layered Models from Video
Abstract. A popular framework for the interpretation of image sequences is the layers or sprite model, see e.g. [1], [2]. Jojic and Frey [3] provide a generative probabilistic mode...
Michalis K. Titsias, Christopher K. I. Williams
ECCV
2008
Springer
14 years 9 months ago
Efficiently Learning Random Fields for Stereo Vision with Sparse Message Passing
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
Jerod J. Weinman, Lam Tran, Christopher J. Pal
CEC
2007
IEEE
14 years 1 months ago
Bayesian inference in estimation of distribution algorithms
— Metaheuristics such as Estimation of Distribution Algorithms and the Cross-Entropy method use probabilistic modelling and inference to generate candidate solutions in optimizat...
Marcus Gallagher, Ian Wood, Jonathan M. Keith, Geo...
ASPDAC
2007
ACM
132views Hardware» more  ASPDAC 2007»
13 years 11 months ago
Fast Decoupling Capacitor Budgeting for Power/Ground Network Using Random Walk Approach
- This paper proposes a fast and practical decoupling capacitor (decap) budgeting algorithm to optimize the power ground (P/G) network design. The new method adopts a modified rand...
Le Kang, Yici Cai, Yi Zou, Jin Shi, Xianlong Hong,...