Free Energy Minimization: A Unified Framework for Modeling, Inference, Learning, and Optimization [Lecture Notes]

Sharu Theresa Jose, Osvaldo Simeone

Research output: Contribution to journalArticlepeer-review

Abstract

The goal of this lecture note is to review the problem of free energy minimization as a unified framework underlying the definition of maximum entropy modeling, generalized Bayesian inference, learning with latent variables, the statistical learning analysis of generalization, and local optimization. Free energy minimization is first introduced, here and historically, as a thermodynamic principle. Then, it is described mathematically in the context of Fenchel duality. Finally, the applications to modeling, inference, learning, and optimization are covered, starting from basic principles.

Original languageEnglish (US)
Article number9363495
Pages (from-to)120-125
Number of pages6
JournalIEEE Signal Processing Magazine
Volume38
Issue number2
DOIs
StatePublished - Mar 2021

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

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