A. Alemi, und I. Fischer. (2018)cite arxiv:1807.04162Comment: Presented at the ICML 2018 workshop on Theoretical Foundations and Applications of Deep Generative Models.
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.
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%0 Generic
%1 alemi2018therml
%A Alemi, Alexander A.
%A Fischer, Ian
%D 2018
%K 2019 arxiv google iclr machine-learning
%T TherML: Thermodynamics of Machine Learning
%U http://arxiv.org/abs/1807.04162
%X 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.
@misc{alemi2018therml,
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.},
added-at = {2019-10-16T15:24:02.000+0200},
author = {Alemi, Alexander A. and Fischer, Ian},
biburl = {https://www.bibsonomy.org/bibtex/233c092bac4cb8bf590111a6ffebc7a46/gujyhu},
description = {[1807.04162] TherML: Thermodynamics of Machine Learning},
interhash = {e7b99adfb92cff7875934f5bdbfe3b78},
intrahash = {33c092bac4cb8bf590111a6ffebc7a46},
keywords = {2019 arxiv google iclr machine-learning},
note = {cite arxiv:1807.04162Comment: Presented at the ICML 2018 workshop on Theoretical Foundations and Applications of Deep Generative Models},
timestamp = {2019-10-16T15:24:07.000+0200},
title = {TherML: Thermodynamics of Machine Learning},
url = {http://arxiv.org/abs/1807.04162},
year = 2018
}