Big Data Optimization: Recent Developments and Challenges
by
 
Emrouznejad, Ali. editor.

Title
Big Data Optimization: Recent Developments and Challenges

Author
Emrouznejad, Ali. editor.

ISBN
9783319302652

Edition
1st ed. 2016.

Physical Description
XV, 487 p. 182 illus., 160 illus. in color. online resource.

Series
Studies in Big Data, 18

Abstract
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.

Subject Term
Computational intelligence.
 
Artificial intelligence.
 
Operations research.
 
Operations Research and Decision Theory.

Added Author
Emrouznejad, Ali.

Added Corporate Author
SpringerLink (Online service)

Electronic Access
https://doi.org/10.1007/978-3-319-30265-2


LibraryMaterial TypeItem BarcodeShelf Number[[missing key: search.ChildField.HOLDING]]Status
Online LibraryE-Book612429-1001ONLINESpringer E-Kitap Koleksiyonu