Asymmetric Boltzmann machines

DOI10.1007/BF00196453zbMath0753.92001OpenAlexW2058079620WikidataQ45246426 ScholiaQ45246426MaRDI QIDQ1181593

B. Appolloni, Alberto Bertoni, Paola Campadelli, Diego de Falco

Publication date: 27 June 1992

Published in: Biological Cybernetics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf00196453

zbMATH Keywords

learning algorithmsLyapunov functioncombinatorial optimizationtime averagesrelative entropy minimizationHebbian ruleasymmetric Boltzmann machinesasymmetric stochastic networksentropic learningfeed-forward architectureNP-complete decision problemstochastic search for global minimatotally antisymmetric parallel network

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Combinatorial optimization (90C27) Neural networks for/in biological studies, artificial life and related topics (92B20) Theory of computing (68Q99)

Related Items (3)

Dynamic sizing of multilayer perceptrons ⋮ Preface ⋮ Visual Recognition and Inference Using Dynamic Overcomplete Sparse Learning

Cites Work

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• Decreasing energy functions as a tool for studying threshold networks
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• The existence of persistent states in the brain
• A generalized convergence theorem for neural networks
• Learning by parallel Boltzmann machines
• Modeling Brain Function
• Positive Automata Networks
• Neural networks and physical systems with emergent collective computational abilities.

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