Big Data Optimization: Recent Developments and Challenges
Format:Paperback
Publisher:Springer International Publishing AG
Published:30th May '18
Currently unavailable, and unfortunately no date known when it will be back
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.
“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)
ISBN: 9783319807652
Dimensions: unknown
Weight: 7548g
487 pages
Softcover reprint of the original 1st ed. 2016