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    Solving Highly Cyclic Distributed Optimization Problems Without Busting the Bank: A Decimation-Based Approach.Jesús Cerquides, Juan Antonio Rodríguez-Aguilar, Rémi Emonet & Gauthier Picard - 2021 - Logic Journal of the IGPL 29 (1):72-95.
    In the context of solving large distributed constraint optimization problems, belief-propagation and incomplete inference algorithms are candidates of choice. However, in general, when the problem structure is very cyclic, these solution methods suffer from bad performance, due to non-convergence and many exchanged messages. As to improve performances of the MaxSum inference algorithm when solving cyclic constraint optimization problems, we propose here to take inspiration from the belief-propagation-guided decimation used to solve sparse random graphs. We propose the novel DeciMaxSum method, which (...)
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