Approximate maximizers of intricacy functionals

DOI10.1007/s00440-011-0350-yzbMath1261.94019arXiv0909.2120OpenAlexW2164550574MaRDI QIDQ714956

Lorenzo Zambotti, Jérôme Buzzi

Publication date: 12 October 2012

Published in: Probability Theory and Related Fields (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0909.2120

zbMATH Keywords

entropymaximizationdiscrete probabilityintricacyneural complexity of a family of random variables

Mathematics Subject Classification ID

Combinatorial probability (60C05) Measures of information, entropy (94A17) Systems biology, networks (92C42)

Related Items (5)

Dynamical intricacy and average sample complexity for random bundle transformations ⋮ Dynamical intricacy and average sample complexity of amenable group actions ⋮ Mean mutual information and symmetry breaking for finite random fields ⋮ Dynamical intricacy and average sample complexity ⋮ Factorized mutual information maximization

Cites Work

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• Mean mutual information and symmetry breaking for finite random fields
• Analytical description of the evolution of neural networks: Learning rules and complexity
• A new class of non-Shannon-type inequalities for entropies
• Information, Physics, and Computation
• The maximal probability that k‐wise independent bits are all 1
• Elements of Information Theory

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