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Units and Layers' Effects on Deep Boltzman Machines

Published: 22 October 2019 Publication History

Abstract

This paper analyzes the units' and layers' effects on deep Boltzman machines. It divides the DBM into two parts and reveals how the two parts affect the DBM's approximation capability. It indicates that the representation power of deep Boltzman machine is not always improved with more units and layers. When a deep Boltzman machine is best already, more units and layers will nearly always lead to worse performance.

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Published In

cover image ACM Other conferences
CSAE '19: Proceedings of the 3rd International Conference on Computer Science and Application Engineering
October 2019
942 pages
ISBN:9781450362948
DOI:10.1145/3331453
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 October 2019

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Author Tags

  1. Approximation capability
  2. Deep Boltzmann machine
  3. Marginal probability distribution

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  • Research-article
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  • Refereed limited

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  • general research projects of Beijing Educations Committee

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CSAE 2019

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Overall Acceptance Rate 368 of 770 submissions, 48%

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