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arXiv · 2411.00135

Iterative Belief Propagation for Sparse Combinatorial Optimization

Sam Reifenstein·Timothée Leleu
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Abstract

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.

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Sam Reifenstein, Timothée Leleu. 2024-10-31. Iterative Belief Propagation for Sparse Combinatorial Optimization. https://arxiv.org/abs/2411.00135

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