Big Data Optimization: Recent Developments and Challenges

Big Data Optimization: Recent Developments and Challenges

English | 2016 | ISBN-10: 3319302639 | 47 pages | EPUB MB

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

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


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