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UAI
1994
13 years 9 months ago
Global Conditioning for Probabilistic Inference in Belief Networks
In this paper we propose a new approach to probabilistic inference on belief networks, global conditioning, which is a simple generalization of Pearl's (1986b) method of loop...
Ross D. Shachter, Stig K. Andersen, Peter Szolovit...
FTDCS
1999
IEEE
14 years 22 days ago
Curricula 2001: A Brief Summary
Model curricula are important resources for curricula planning and design. A joint task force between IEEE-CS and ACM wasformed to undertake the responsibility of revising the 199...
Francis C. M. Lau, Carl K. Chang
TIT
2008
129views more  TIT 2008»
13 years 8 months ago
Serial Schedules for Belief-Propagation: Analysis of Convergence Time
Abstract--Low-Density Parity-Check (LDPC) codes are usually decoded by running an iterative belief-propagation algorithm over the factor graph of the code. In the traditional messa...
Jacob Goldberger, Haggai Kfir
CVPR
2009
IEEE
1468views Computer Vision» more  CVPR 2009»
15 years 3 months ago
Hardware-Efficient Belief Propagation
Belief propagation (BP) is an effective algorithm for solving energy minimization problems in computer vision. However, it requires enormous memory, bandwidth, and computation beca...
Chao-Chung Cheng, Chia-Kai Liang, Homer H. Chen, L...
PODC
1994
ACM
14 years 15 days ago
Using Belief to Reason about Cache Coherence
The notion of belief has been useful in reasoning about authentication protocols. In this paper, we show how the notion of belief can be applied to reasoning about cache coherence...
Lily B. Mummert, Jeannette M. Wing, Mahadev Satyan...