The Entropy Economy and the Kolmogorov Learning Cycle: Leveraging the intersection of Machine Learning and Algorithmic Information Theory to jointly optimize energy and learning-Reference-Cited by-同舟云学术

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The Entropy Economy and the Kolmogorov Learning Cycle: Leveraging the intersection of Machine Learning and Algorithmic Information Theory to jointly optimize energy and learning

Published:2024-05 Issue: Volume:461 Page:134051
ISSN:0167-2789
Container-title:Physica D: Nonlinear Phenomena
language:en
Short-container-title:Physica D: Nonlinear Phenomena

Author:

Evans Scott C.^ORCID,Shah Tapan,Huang Hao,Ekanayake Sachini Piyoni

Funder

U.S. Department of Energy

Publisher

Elsevier BV

Reference33 articles.

1. Information is physical;Landauer;Phys. Today,1991

2. Logical reversibility of computation;Bennett;IBM J. Res. Develop.,1973

3. The thermodynamics of computation A review;Bennett;Int. J. Theor. Phys.,1982

4. Stochastic thermodynamics of computation;Wolpert;J. Phys.: Mathe. Theor.,2019

5. D.H. Wolpert, “Extending Landauer's bound from bit erasure to arbitrary computation,” https://arxiv.org/abs/1508.05319, Submitted on 21 Aug 2015 (v1), last revised 24 Nov 2015 (this version, v4)].

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