Big Data Optimization: Recent Developments and Challenges
Editors: Emrouznejad, Ali (Ed.)
Free Preview- Presents recent developments and challenges in big data optimization
- Collects various recent algorithms in large-scale optimization all in one book
- Presents useful big data optimization applications in a variety of industries, both for academics and practitioners
- Include some guideline to use cloud computing and Hadoop in large-scale and big data optimization
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- About this book
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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.
- Reviews
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“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)
- Download Preface 1 PDF (81.5 KB)
- Download Sample pages 2 PDF (513.8 KB)
- Download Table of contents PDF (56.2 KB)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Big Data Optimization: Recent Developments and Challenges
- Editors
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- Ali Emrouznejad
- Series Title
- Studies in Big Data
- Series Volume
- 18
- Copyright
- 2016
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing Switzerland
- eBook ISBN
- 978-3-319-30265-2
- DOI
- 10.1007/978-3-319-30265-2
- Hardcover ISBN
- 978-3-319-30263-8
- Softcover ISBN
- 978-3-319-80765-2
- Series ISSN
- 2197-6503
- Edition Number
- 1
- Number of Pages
- XV, 487
- Number of Illustrations
- 22 b/w illustrations, 160 illustrations in colour
- Topics
