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

Softcover

ISBN 10: 331980765X ISBN 13: 9783319807652

Publisher: Springer, 2018

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.

About this title

From the Back Cover

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.

Edition details

• Publisher: Springer
• Publication date: 2018
• Language: English
• ISBN 10: 331980765X
• ISBN 13: 9783319807652
• Binding: Paperback
• Number of pages: 502
• Editor: Emrouznejad Ali