Big Data Optimization: Recent Developments and Challenges - Studies in Big Data
Big Data Optimization: Recent Developments and Challenges - Studies in Big Data
hardback
Published:
7 June, 2016
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Description
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.
More Details
| Type | Book |
|---|---|
| ISBN13 | 9783319302638 |
| ISBN10 | 3319302639 |
| Number Of Pages | 487 |
| Item Weight | 1000 g |
| Publisher / Reseller | Springer International Publishing AG |
| Format | hardback |
| Edition | 1st ed. 2016 |
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)