Ensembles of Networks Produced from Neural Architecture Search

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

Neural architecture search (NAS) is a popular topic at the intersection of deep learning and high performance computing. NAS focuses on optimizing the architecture of neural networks along with their hyperparameters in order to produce networks with superior performance. Much of the focus has been on how to produce a single best network to solve a machine learning problem, but as NAS methods produce many networks that work very well, this affords the opportunity to ensemble these networks to produce an improved result. Additionally, the diversity of network structures produced by NAS drives a natural bias towards diversity of predictions produced by the individual networks. This results in an improved ensemble over simply creating an ensemble that contains duplicates of the best network architecture retrained to have unique weights.

Original languageEnglish
Title of host publicationHigh Performance Computing - ISC High Performance 2020 International Workshops, Revised Selected Papers
EditorsHeike Jagode, Hartwig Anzt, Guido Juckeland, Hatem Ltaief
PublisherSpringer Science and Business Media Deutschland GmbH
Pages223-234
Number of pages12
ISBN (Print)9783030598501
DOIs
StatePublished - 2020
Event35th International Conference on High Performance Computing , ISC High Performance 2020 - Frankfurt am Main, Germany
Duration: Jun 21 2020Jun 25 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12321 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference35th International Conference on High Performance Computing , ISC High Performance 2020
Country/TerritoryGermany
CityFrankfurt am Main
Period06/21/2006/25/20

Funding

This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, Robinson Pino, program manager, under contract number DE-AC05-00OR22725. This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725.

FundersFunder number
U.S. Department of Energy
Office of Science
Advanced Scientific Computing ResearchDE-AC05-00OR22725

    Keywords

    • Ensembles
    • High performance computing
    • Neural architecture search

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