Téléchargez le livre : Black Box Optimization, Machine Learning, and No-Free Lunch Theorems

Black Box Optimization, Machine Learning, and No-Free Lunch Theorems



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Éditeur :

Springer


Collection :

Springer Optimization and Its Applications

Paru le : 2021-05-27



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Description



This edited volume illustrates the connections between machine learning techniques, black box optimization, and no-free lunch theorems. Each of the thirteen contributions focuses on the commonality and interdisciplinary concepts as well as the fundamentals needed to fully comprehend the impact of individual applications and problems.  Current theoretical, algorithmic, and practical methods used are provided to stimulate a new effort towards innovative and efficient solutions. The book is intended for beginners who wish to achieve a broad overview of optimization methods and also for more experienced researchers as well as researchers in mathematics, optimization, operations research, quantitative logistics, data analysis, and statistics, who will benefit from access to a quick reference to key topics and methods. The coverage ranges from mathematically rigorous methods to heuristic and evolutionary approaches in an attempt to equip the reader with different viewpoints of the same problem.
Pages
388 pages
Collection
Springer Optimization and Its Applications
Parution
2021-05-27
Marque
Springer
EAN papier
9783030665142
EAN PDF
9783030665159
Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
38
Taille du fichier
7680 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
126,59 €
EAN EPUB
9783030665159
Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
38
Taille du fichier
23091 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
126,59 €

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