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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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Detaylı Bibliyografya
Müşterek Yazar: SpringerLink (Online service)
Diğer Yazarlar: Emrouznejad, Ali (Editör)
Materyal Türü: e-Kitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Cham : Springer International Publishing : 2016.
Imprint: Springer,
Edisyon:1st ed. 2016.
Seri Bilgileri:Studies in Big Data, 18
Konular:
Online Erişim:Full-text access
Diğer Bilgiler
Özet: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.
Fiziksel Özellikler:XV, 487 p. 182 illus., 160 illus. in color. online resource.
ISBN:9783319302652
ISSN:2197-6511 ;
DOI:10.1007/978-3-319-30265-2