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» Approximability of Probability Distributions
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130
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CORR
2006
Springer
104views Education» more  CORR 2006»
15 years 2 months ago
Loop corrections for approximate inference
We propose a method to improve approximate inference methods by correcting for the influence of loops in the graphical model. The method is a generalization and alternative implem...
Joris M. Mooij, Bert Kappen
121
Voted
FOCS
2005
IEEE
15 years 8 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Chaitanya Swamy, David B. Shmoys
126
Voted
DAGSTUHL
2007
15 years 4 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic Optimization
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Chaitanya Swamy, David B. Shmoys
102
Voted
INFOCOM
2010
IEEE
15 years 1 months ago
Markov Approximation for Combinatorial Network Optimization
—Many important network design problems can be formulated as a combinatorial optimization problem. A large number of such problems, however, cannot readily be tackled by distribu...
Minghua Chen, Soung Chang Liew, Ziyu Shao, Caihong...
116
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IAT
2006
IEEE
15 years 8 months ago
Using Prior Knowledge to Improve Distributed Hill Climbing
The Distributed Probabilistic Protocol (DPP) is a new, approximate algorithm for solving Distributed Constraint Satisfaction Problems (DCSPs) that exploits prior knowledge to impr...
Roger Mailler