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arXiv:1807.04162cs.LG

TherML: Thermodynamics of Machine Learning

Alexander A. Alemi, Ian Fischer

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Abstract

In this work we offer a framework for reasoning about a wide class of existing objectives in machine learning. We develop a formal correspondence between this work and thermodynamics and discuss its implications.

arXiv comments
Presented at the ICML 2018 workshop on Theoretical Foundations and Applications of Deep Generative Models
Journal reference
DOI
Subjects
cs.LGMachine Learning cond-mat.stat-mechStatistical Mechanics stat.MLMachine Learning (Statistics)

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