Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 400 pp. Englisch. Seller Inventory # 9783030665173

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

Published by Springer International Publishing, 2022

ISBN 10: 3030665178 ISBN 13: 9783030665173

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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Beginners will achieve an overview of optimization methodsResearchers will gain access to to a useful reference on key topicsMathematical rigour and heuristics approaches equip the reader with different viewpoints on the same problem. Seller Inventory # 608128385

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

Panos M. Pardalos

Published by Springer International Publishing, 2022

ISBN 10: 3030665178 ISBN 13: 9783030665173

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Seller: AHA-BUCH GmbH, Einbeck, Germany

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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Seller Inventory # 9783030665173

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