A Block Successive Lower-Bound Maximization Algorithm for the Maximum Pseudo-Likelihood Estimation of Fully Visible Boltzmann Machines

DOI10.1162/NECO_a_00813zbMath1472.68151OpenAlexW2231657818WikidataQ50743144 ScholiaQ50743144MaRDI QIDQ5380400

Ian A. Wood, Hien Duy Nguyen

Publication date: 4 June 2019

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1162/neco_a_00813

Mathematics Subject Classification ID

Point estimation (62F10) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

Near universal consistency of the maximum pseudolikelihood estimator for discrete models

Cites Work

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• A Unified Convergence Analysis of Block Successive Minimization Methods for Nonsmooth Optimization
• Consistency of Pseudolikelihood Estimation of Fully Visible Boltzmann Machines
• A Simplex Method for Function Minimization
• Optimization

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