Adaptive Thouless-Anderson-Palmer equation for higher-order Markov random fields

Chako Takahashi, Muneki Yasuda, Kazuyuki Tanaka

Research output: Contribution to journalArticlepeer-review

Abstract

The adaptive Thouless-Anderson-Palmer (TAP) mean-field approximation is one of the advanced mean-field approaches, and it is known as a powerful accurate method for Markov random fields (MRFs) with quadratic interactions (pairwise MRFs). In this study, an extension of the adaptive TAP approximation for MRFs with many-body interactions (higher-order MRFs) is developed. We show that the adaptive TAP equation for pairwise MRFs is derived by naive mean-field approximation with diagonal consistency. Based on the equivalence of the approximate equation obtained from the naive mean-field approximation with diagonal consistency and the adaptive TAP equation in pairwise MRFs, we formulate approximate equations for higher-order Boltzmann machines, which is one of simplest higher-order MRFs, via the naive mean-field approximation with diagonal consistency.

Original languageEnglish
Article number064007
Journaljournal of the physical society of japan
Volume89
Issue number6
DOIs
Publication statusPublished - 2020 Jun

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Fingerprint

Dive into the research topics of 'Adaptive Thouless-Anderson-Palmer equation for higher-order Markov random fields'. Together they form a unique fingerprint.

Cite this