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» Belief Update Using Graphs
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ECAI
2010
Springer
13 years 10 months ago
Foundations of Tree-like Local Model Updates
Abstract. Model update is an approach to enhance model checking functions by providing computer aided modifications in system development [2, 9]. It has been observed that one majo...
Yan Zhang, Michael Kelly, Yi Zhou
SDM
2007
SIAM
139views Data Mining» more  SDM 2007»
13 years 11 months ago
Dynamic Algorithm for Graph Clustering Using Minimum Cut Tree
We present an efficient dynamic algorithm for clustering undirected graphs, whose edge property is changing continuously. The algorithm maintains clusters of high quality in pres...
Barna Saha, Pabitra Mitra
AMAI
2004
Springer
14 years 3 months ago
Using the Central Limit Theorem for Belief Network Learning
Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
Ian Davidson, Minoo Aminian
TIT
2008
129views more  TIT 2008»
13 years 9 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
ICTAI
2005
IEEE
14 years 3 months ago
Planning with POMDPs Using a Compact, Logic-Based Representation
Partially Observable Markov Decision Processes (POMDPs) provide a general framework for AI planning, but they lack the structure for representing real world planning problems in a...
Chenggang Wang, James G. Schmolze