Big Data Optimization: Recent Developments and Challenges: 18 - Rilegato
Libro 15 di 95: Studies in Big Data
Sinossi
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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Dalla quarta di copertina
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.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Big Data Optimization: Recent Developments and Challenges (eng)
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Big Data Optimization: Recent Developments and Challenges
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Springer International Publishing, 2016
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ISBN 13: 9783319302638
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Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 academi. Codice articolo 117040900
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Big Data Optimization: Recent Developments and Challenges
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Springer International Publishing Jun 2016, 2016
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 504 pp. Englisch. Codice articolo 9783319302638
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Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 504 pp. Englisch. Codice articolo 9783319302638
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Big Data Optimization: Recent Developments and Challenges
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Codice articolo 9783319302638
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