Expected energy-based restricted Boltzmann machine for classification

DOI10.1016/j.neunet.2014.09.006zbMath1325.68185DBLPjournals/nn/ElfwingUD15OpenAlexW2048865854WikidataQ44463509 ScholiaQ44463509MaRDI QIDQ890738

Kenji Doya, S. Elfwing, Eiji Uchibe

Publication date: 11 November 2015

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

Full work available at URL: https://doi.org/10.1016/j.neunet.2014.09.006

zbMATH Keywords

classificationfree energyrestricted Boltzmann machineexpected energy

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (2)

Convex and concave envelopes of artificial neural network activation functions for deterministic global optimization ⋮ A mathematical discussion concerning the performance of multilayer perceptron-type artificial neural networks through use of orthogonal bipolar vectors

Uses Software

• darch

Cites Work

• Reducing the Dimensionality of Data with Neural Networks
• Training Products of Experts by Minimizing Contrastive Divergence
• A Fast Learning Algorithm for Deep Belief Nets
• Training invariant support vector machines
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