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Loopy Belief Propagation and Gibbs Measures
 In Uncertainty in Artificial Intelligence
, 2002
"... We address the question of convergence in the loopy belief propagation (LBP) algorithm. ..."
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Cited by 103 (6 self)
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We address the question of convergence in the loopy belief propagation (LBP) algorithm.
Hybrid loopy belief propagation
 In Proceedings of the Third European Workshop on Probabilistic Graphical Models (PGM'06
, 2006
"... We propose an algorithm called Hybrid Loopy Belief Propagation (HLBP), which extends the Loopy Belief Propagation (LBP) (Murphy et al., 1999) and Nonparametric Belief Propagation (NBP) (Sudderth et al., 2003) algorithms to deal with general hybrid Bayesian networks. The main idea is to represent the ..."
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Cited by 8 (2 self)
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We propose an algorithm called Hybrid Loopy Belief Propagation (HLBP), which extends the Loopy Belief Propagation (LBP) (Murphy et al., 1999) and Nonparametric Belief Propagation (NBP) (Sudderth et al., 2003) algorithms to deal with general hybrid Bayesian networks. The main idea is to represent
Loopy Belief Propagation for Approximate Inference: An Empirical Study
 In Proceedings of Uncertainty in AI
, 1999
"... Recently, researchers have demonstrated that "loopy belief propagation"  the use of Pearl's polytree algorithm in a Bayesian network with loops  can perform well in the context of errorcorrecting codes. The most dramatic instance of this is the near Shannonlimit performa ..."
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Cited by 680 (18 self)
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Recently, researchers have demonstrated that "loopy belief propagation"  the use of Pearl's polytree algorithm in a Bayesian network with loops  can perform well in the context of errorcorrecting codes. The most dramatic instance of this is the near Shannon
Loopy Belief Propagation in the Presence of Determinism
"... It is well known that loopy Belief propagation (LBP) performs poorly on probabilistic graphical models (PGMs) with determinism. In this paper, we propose a new method for remedying this problem. The key idea in our method is finding a reparameterization of the graphical model such that LBP, when r ..."
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It is well known that loopy Belief propagation (LBP) performs poorly on probabilistic graphical models (PGMs) with determinism. In this paper, we propose a new method for remedying this problem. The key idea in our method is finding a reparameterization of the graphical model such that LBP, when
Very Loopy Belief Propagation for Unwrapping Phase Images
, 2001
"... Since the discovery that the best errorcorrecting decoding algorithm can be viewed as belief propagation in a cyclebound graph, researchers have been trying to determine under what circumstances "loopy belief propagation" is eective for probabilistic inference. Despite several ..."
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Cited by 33 (4 self)
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Since the discovery that the best errorcorrecting decoding algorithm can be viewed as belief propagation in a cyclebound graph, researchers have been trying to determine under what circumstances "loopy belief propagation" is eective for probabilistic inference. Despite several
On the Uniqueness of Loopy Belief Propagation Fixed Points
, 2004
"... We derive sufficient conditions for the uniqueness of loopy belief propagation fixed points. These conditions depend on both the structure of the graph and the strength of the potentials and naturally extend those for convexity of the Bethe free energy. We compare them with (a strengthened version o ..."
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Cited by 77 (2 self)
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We derive sufficient conditions for the uniqueness of loopy belief propagation fixed points. These conditions depend on both the structure of the graph and the strength of the potentials and naturally extend those for convexity of the Bethe free energy. We compare them with (a strengthened version
Sufficient conditions for convergence of loopy belief propagation
 In Proc. Conference on Uncertainty in Artificial Intelligence (UAI
, 2005
"... We derive novel conditions that guarantee convergence of Loopy Belief Propagation (also known as the SumProduct algorithm) to a unique fixed point. Our results are provably stronger than existing sufficient conditions. We show that the improvement can be quite substantial; in particular, for binary ..."
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Cited by 30 (3 self)
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We derive novel conditions that guarantee convergence of Loopy Belief Propagation (also known as the SumProduct algorithm) to a unique fixed point. Our results are provably stronger than existing sufficient conditions. We show that the improvement can be quite substantial; in particular
A Parallel Framework For Loopy Belief Propagation ABSTRACT
"... There are many innovative proposals introduced in the literature under the evolutionary computation field, from which estimation of distribution algorithms (EDAs) is one of them. Their main characteristic is the use of probabilistic models to represent the (in)dependencies between the variables of a ..."
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Cited by 13 (0 self)
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, are belief propagation algorithms. In this paper we present a parallel approach for one of these inferencebased algorithms, the loopy belief propagation algorithm for factor graphs. Our parallel implementation was designed to provide an algorithm that can be executed in clusters of computers
Stable fixed points of loopy belief propagation are minima of the Bethe free energy
, 2002
"... We extend recent work on the connection between loopy belief propagation and the Bethe free energy. Constrained minimization of the Bethe free energy can be turned into an unconstrained saddlepoint problem. Both converging doubleloop algorithms and standard loopy belief propagation can be interpre ..."
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Cited by 71 (8 self)
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We extend recent work on the connection between loopy belief propagation and the Bethe free energy. Constrained minimization of the Bethe free energy can be turned into an unconstrained saddlepoint problem. Both converging doubleloop algorithms and standard loopy belief propagation can
Results 1  10
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90,549