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arXiv · 1611.09428

Stochastic Thermodynamics of Learning

Sebastian Goldt·Udo Seifert
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Abstract

Virtually every organism gathers information about its noisy environment and builds models from that data, mostly using neural networks. Here, we use stochastic thermodynamics to analyse the learning of a classification rule by a neural network. We show that the information acquired by the network is bounded by the thermodynamic cost of learning and introduce a learning efficiency $η\le1$. We discuss the conditions for optimal learning and analyse Hebbian learning in the thermodynamic limit.

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BibTeXRIS

Sebastian Goldt, Udo Seifert. 2016-11-28. Stochastic Thermodynamics of Learning. https://doi.org/10.1103/physrevlett.118.010601

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