Big Data Optimization: Recent Developments and Challenges (Paperback, Softcover reprint of the original 1st ed. 2016)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Studies in Big Data, 18
Release date:	May 2018
First published:	2016
Editors:	Ali Emrouznejad
Dimensions:	235 x 155 x 26mm (L x W x T)
Format:	Paperback
Pages:	487
Edition:	Softcover reprint of the original 1st ed. 2016
ISBN-13:	978-3-319-80765-2
Categories:	Books > Business & Economics > Business & management > Management & management techniques > Operational research Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-319-80765-X
Barcode:	9783319807652

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