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Multi-Objective Decision Making (Synthesis Lectures on Artificial Intelligence and Machine Learning)
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Multi-Objective Decision Making (Synthesis Lectures on Artificial Intelligence and Machine Learning)
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Multi-Objective Decision Making (Synthesis Lectures on Artificial Intelligence and Machine Learning)
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Multi-Objective Decision Making (Synthesis Lectures on Artificial Intelligence and Machine Learning)
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Multi-Objective Decision Making (Synthesis Lectures on Artificial Intelligence and Machine Learning)
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Machine Learning Assisted Evolutionary Multi- and Many- Objective Optimization (Genetic and Evolutionary Computation)
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Multi-Objective Machine Learning
Published by Springer-Verlag GmbH, 2006
ISBN 10: 3540306765 ISBN 13: 9783540306764
Language: English
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Machine Learning Assisted Evolutionary Multi and Many Objective Optimization
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Machine Learning Assisted Evolutionary Multi- and Many- Objective Optimization
Published by Springer, Berlin|Springer Nature Singapore|Springer, 2023
ISBN 10: 9819920957 ISBN 13: 9789819920952
Language: English
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Machine Learning Assisted Evolutionary Multi and Many Objective Optimization
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Multi-Objective Machine Learning (Studies in Computational Intelligence, 16)
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Multi-Objective Machine Learning (Studies in Computational Intelligence, 16)
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Machine Learning Assisted Evolutionary Multi- and Many- Objective Optimization
Published by Springer Nature Singapore, Springer Nature Singapore Mai 2024, 2024
ISBN 10: 9819920957 ISBN 13: 9789819920952
Language: English
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Add to basketBuch. Condition: Neu. Neuware -This book focuses on machine learning (ML) assisted evolutionary multi- and many-objective optimization (EMâO). EMâO algorithms, namely EMâOAs, iteratively evolve a set of solutions towards a good Pareto Front approximation. The availability of multiple solution sets over successive generations makes EMâOAs amenable to application of ML for different pursuits.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 260 pp. Englisch.
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hardcover. Condition: New. In shrink wrap. Looks like an interesting title!
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Machine Learning Assisted Evolutionary Multi- and Many- Objective Optimization
Published by Springer Nature Singapore, Springer Nature Singapore, 2024
ISBN 10: 9819920957 ISBN 13: 9789819920952
Language: English
US$ 212.82
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Add to basketBuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book focuses on machine learning (ML) assisted evolutionary multi- and many-objective optimization (EMâO). EMâO algorithms, namely EMâOAs, iteratively evolve a set of solutions towards a good Pareto Front approximation. The availability of multiple solution sets over successive generations makes EMâOAs amenable to application of ML for different pursuits.Recognizing the immense potential for ML-based enhancements in the EMâO domain, this book intends to serve as an exclusive resource for both domain novices and the experienced researchers and practitioners.To achieve this goal, the book first covers the foundations of optimization, including problem and algorithm types.Then, well-structured chapters present some of the key studies on ML-based enhancements in the EMâO domain, systematically addressing important aspects. These include learning to understand the problem structure, converge better, diversify better, simultaneously converge and diversify better, and analyze the Pareto Front. In doing so, this book broadly summarizes the literature, beginning with foundational work on innovization (2003) and objective reduction (2006), and extending to the most recently proposed innovized progress operators (2021-23). It also highlights the utility of ML interventions in the search, post-optimality, and decision-making phases pertaining to the use of EMâOAs. Finally, this book shares insightful perspectives on the future potential for ML based enhancements in the EMâOA domain.To aid readers, the book includes working codes for the developed algorithms. This book will not only strengthen this emergent theme but also encourage ML researchers to develop more efficient and scalable methods that cater to the requirements of the EMâOA domain. It serves as an inspiration for further research and applications at the synergistic intersection of EMâOA and ML domains.
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Multi-Objective Machine Learning
Published by Springer Berlin Heidelberg, 2010
ISBN 10: 3642067964 ISBN 13: 9783642067969
Language: English
US$ 179.08
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Condition: New. pp. 676.
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Machine Learning Assisted Evolutionary Multi and Many Objective Optimization
Published by Springer-Nature New York Inc, 2024
ISBN 10: 9819920957 ISBN 13: 9789819920952
Language: English
US$ 288.36
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Add to basketHardcover. Condition: Brand New. 259 pages. 9.25x6.10x9.21 inches. In Stock.
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US$ 316.07
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Add to basketCondition: New. pp. 676 Illus.
