Big Data Optimization: Recent Developments and Challenges: 18 (Studies in Big Data)

Big Data Optimization: Recent Developments and Challenges: 18 (Studies in Big Data)

by Ali Emrouznejad (Editor)

Synopsis

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.

$212.70

Quantity

20+ in stock

More Information

Format: Hardcover
Pages: 504
Edition: 1st ed. 2016
Publisher: Springer
Published: 18 May 2016

ISBN 10: 3319302639
ISBN 13: 9783319302638

Media Reviews
It can be used as a reference book on big data, to obtain a broad view of the direction and landscape. In addition, it can be used by specialists in specific areas of big data, especially optimization-related areas. In this respect, the preview of chapter titles and brief explanations provided in this review reveal specific areas of interest for the intended specialists. I like this edited volume and recommend it. (M. M. Tanik, Computing Reviews, January, 2017)