Iterative Belief Propagation for Sparse Combinatorial Optimization

Fuente: arXiv
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Main Authors: Reifenstein, Sam, Leleu, Timothée
Format: Preprint
Published: 2024
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author Reifenstein, Sam
Leleu, Timothée
author_facet Reifenstein, Sam
Leleu, Timothée
contents In this note we study an iterative belief propagation (IBP) algorithm and demonstrate it's ability to solve sparse combinatorial optimization problems. Similar to simulated annealing (SA), our IBP algorithm attempts to sample from the Boltzmann distribution of the objective function but also uses belief propagation (BP) to improve convergence.
format Preprint
id arxiv_https___arxiv_org_abs_2411_00135
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Iterative Belief Propagation for Sparse Combinatorial Optimization
Reifenstein, Sam
Leleu, Timothée
Optimization and Control
In this note we study an iterative belief propagation (IBP) algorithm and demonstrate it's ability to solve sparse combinatorial optimization problems. Similar to simulated annealing (SA), our IBP algorithm attempts to sample from the Boltzmann distribution of the objective function but also uses belief propagation (BP) to improve convergence.
title Iterative Belief Propagation for Sparse Combinatorial Optimization
topic Optimization and Control
url https://arxiv.org/abs/2411.00135