Understanding the dynamics of message passing algorithms: a free probability heuristics

• URL: http://arxiv.org/abs/2002.02533v1
• Date: Mon, 3 Feb 2020 19:50:31 GMT
• Title: Understanding the dynamics of message passing algorithms: a free probability heuristics
• Authors: Manfred Opper and Burak \c{C}akmak
• Abstract summary: We analyze the behavior of inference algorithms for probabilistic models with dense coupling matrices in the limit of large systems. For a toy Ising model, we are able to recover previous results such as the property of vanishing effective memories and the analytical convergence rate of the algorithm.
• Score: 2.8021833233819486
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We use freeness assumptions of random matrix theory to analyze the dynamical behavior of inference algorithms for probabilistic models with dense coupling matrices in the limit of large systems. For a toy Ising model, we are able to recover previous results such as the property of vanishing effective memories and the analytical convergence rate of the algorithm.

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