Stochastic Thermodynamics of Learning.

  title={Stochastic Thermodynamics of Learning.},
  author={Sebastian Goldt and U. Seifert},
  journal={Physical review letters},
  volume={118 1},
Virtually every organism gathers information about its noisy environment and builds models from those data, mostly using neural networks. Here, we use stochastic thermodynamics to analyze 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≤1. We discuss the conditions for optimal learning and analyze Hebbian learning in the thermodynamic limit. 
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