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arXiv · 2009.14702

Some Remarks on Replicated Simulated Annealing

Vincent Gripon·Matthias Löwe·Franck Vermet
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Abstract

Recently authors have introduced the idea of training discrete weights neural networks using a mix between classical simulated annealing and a replica ansatz known from the statistical physics literature. Among other points, they claim their method is able to find robust configurations. In this paper, we analyze this so-called "replicated simulated annealing" algorithm. In particular, we explicit criteria to guarantee its convergence, and study when it successfully samples from configurations. We also perform experiments using synthetic and real data bases.

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BibTeXRIS

Vincent Gripon, Matthias Löwe, Franck Vermet. 2020-09-30. Some Remarks on Replicated Simulated Annealing. https://doi.org/10.1007/s10955-021-02727-z

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