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Big data optimization recent developments and challenges

The main objective of this book is to provide the necessary background to work with big data by introducing some novel optimization algorithms and codes capable of working in the big data setting as well as introducing some applications in big data optimization for both academics and practitioners i...

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Detalles Bibliográficos
Autor principal: Emrouznejad, Ali
Lenguaje:eng
Publicado: Springer 2016
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-30265-2
http://cds.cern.ch/record/2157642
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author Emrouznejad, Ali
author_facet Emrouznejad, Ali
author_sort Emrouznejad, Ali
collection CERN
description The main objective of this book is to provide the necessary background to work with big data by introducing some novel optimization algorithms and codes capable of working in the big data setting as well as introducing some applications in big data optimization for both academics and practitioners interested, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book will be useful for the researchers aiming to analyses large scale data. Several optimization algorithms for big data including convergent parallel algorithms, limited memory bundle algorithm, diagonal bundle method, convergent parallel algorithms, network analytics, and many more have been explored in this book.
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institution Organización Europea para la Investigación Nuclear
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spelling cern-21576422021-04-21T19:40:59Zdoi:10.1007/978-3-319-30265-2http://cds.cern.ch/record/2157642engEmrouznejad, AliBig data optimization recent developments and challengesEngineeringThe main objective of this book is to provide the necessary background to work with big data by introducing some novel optimization algorithms and codes capable of working in the big data setting as well as introducing some applications in big data optimization for both academics and practitioners interested, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book will be useful for the researchers aiming to analyses large scale data. Several optimization algorithms for big data including convergent parallel algorithms, limited memory bundle algorithm, diagonal bundle method, convergent parallel algorithms, network analytics, and many more have been explored in this book.Springeroai:cds.cern.ch:21576422016
spellingShingle Engineering
Emrouznejad, Ali
Big data optimization recent developments and challenges
title Big data optimization recent developments and challenges
title_full Big data optimization recent developments and challenges
title_fullStr Big data optimization recent developments and challenges
title_full_unstemmed Big data optimization recent developments and challenges
title_short Big data optimization recent developments and challenges
title_sort big data optimization recent developments and challenges
topic Engineering
url https://dx.doi.org/10.1007/978-3-319-30265-2
http://cds.cern.ch/record/2157642
work_keys_str_mv AT emrouznejadali bigdataoptimizationrecentdevelopmentsandchallenges