The Problem Of Tuning Metaheuristics As Seen From A Machine Learning Perspective

Author : Mauro Birattari
Publisher : IOS Press
ISBN 13 : 9781586035518
Total Pages : 0 pages
Book Rating : 4.17/5 ( download)

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Download or read book The Problem of Tuning Metaheuristics as Seen from a Machine Learning Perspective written by Mauro Birattari and published by IOS Press. This book was released on 2005 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A metaheuristic is a generic algorithmic template that can be used for finding high quality solutions of optimization problems. The authors show that the problem of tuning a metaheuristic can be described and solved as a machine learning problem. This thesis contains an experimental analysis of F-Race and some examples of practical applications."

Author : Mauro Birattari
Publisher :
ISBN 13 : 9783898382922
Total Pages : 292 pages
Book Rating : 4.23/5 ( download)

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Download or read book The Problem of Tuning Metaheuristics written by Mauro Birattari and published by . This book was released on 2005 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : Mauro Birattari
Publisher : Springer
ISBN 13 : 3642004830
Total Pages : 226 pages
Book Rating : 4.34/5 ( download)

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Download or read book Tuning Metaheuristics written by Mauro Birattari and published by Springer. This book was released on 2009-05-02 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book lays the foundations for a scientific approach to tuning metaheuristics. The fundamental intuition that underlies Birattari's approach is that the tuning problem has much in common with the problems that are typically faced in machine learning.

Author : Mauro Birattari
Publisher : Springer Science & Business Media
ISBN 13 : 3642004822
Total Pages : 226 pages
Book Rating : 4.27/5 ( download)

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Download or read book Tuning Metaheuristics written by Mauro Birattari and published by Springer Science & Business Media. This book was released on 2009-04-08 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book lays the foundations for a scientific approach to tuning metaheuristics. The fundamental intuition that underlies Birattari's approach is that the tuning problem has much in common with the problems that are typically faced in machine learning.

Author : Kanak Kalita
Publisher : John Wiley & Sons
ISBN 13 : 1394233930
Total Pages : 272 pages
Book Rating : 4.39/5 ( download)

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Download or read book Metaheuristics for Machine Learning written by Kanak Kalita and published by John Wiley & Sons. This book was released on 2024-03-28 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: METAHEURISTICS for MACHINE LEARNING The book unlocks the power of nature-inspired optimization in machine learning and presents a comprehensive guide to cutting-edge algorithms, interdisciplinary insights, and real-world applications. The field of metaheuristic optimization algorithms is experiencing rapid growth, both in academic research and industrial applications. These nature-inspired algorithms, which draw on phenomena like evolution, swarm behavior, and neural systems, have shown remarkable efficiency in solving complex optimization problems. With advancements in machine learning and artificial intelligence, the application of metaheuristic optimization techniques has expanded, demonstrating significant potential in optimizing machine learning models, hyperparameter tuning, and feature selection, among other use-cases. In the industrial landscape, these techniques are becoming indispensable for solving real-world problems in sectors ranging from healthcare to cybersecurity and sustainability. Businesses are incorporating metaheuristic optimization into machine learning workflows to improve decision-making, automate processes, and enhance system performance. As the boundaries of what is computationally possible continue to expand, the integration of metaheuristic optimization and machine learning represents a pioneering frontier in computational intelligence, making this book a timely resource for anyone involved in this interdisciplinary field. Metaheuristics for Machine Learning: Algorithms and Applications serves as a comprehensive guide to the intersection of nature-inspired optimization and machine learning. Authored by leading experts, this book seamlessly integrates insights from computer science, biology, and mathematics to offer a panoramic view of the latest advancements in metaheuristic algorithms. You’ll find detailed yet accessible discussions of algorithmic theory alongside real-world case studies that demonstrate their practical applications in machine learning optimization. Perfect for researchers, practitioners, and students, this book provides cutting-edge content with a focus on applicability and interdisciplinary knowledge. Whether you aim to optimize complex systems, delve into neural networks, or enhance predictive modeling, this book arms you with the tools and understanding you need to tackle challenges efficiently. Equip yourself with this essential resource and navigate the ever-evolving landscape of machine learning and optimization with confidence. Audience The book is aimed at a broad audience encompassing researchers, practitioners, and students in the fields of computer science, data science, engineering, and mathematics. The detailed but accessible content makes it a must-have for both academia and industry professionals interested in the optimization aspects of machine learning algorithms.

Author : Karl F. Doerner
Publisher : Springer Science & Business Media
ISBN 13 : 0387719210
Total Pages : 409 pages
Book Rating : 4.14/5 ( download)

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Download or read book Metaheuristics written by Karl F. Doerner and published by Springer Science & Business Media. This book was released on 2007-08-13 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book’s aim is to provide several different kinds of information: a delineation of general metaheuristics methods, a number of state-of-the-art articles from a variety of well-known classical application areas as well as an outlook to modern computational methods in promising new areas. Therefore, this book may equally serve as a textbook in graduate courses for students, as a reference book for people interested in engineering or social sciences, and as a collection of new and promising avenues for researchers working in this field.

Author : Marco Dorigo
Publisher : Springer
ISBN 13 : 3540875271
Total Pages : 430 pages
Book Rating : 4.77/5 ( download)

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Download or read book Ant Colony Optimization and Swarm Intelligence written by Marco Dorigo and published by Springer. This book was released on 2008-09-20 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: The series of biannual international conferences “ANTS – International C- ference on Ant Colony Optimization and Swarm Intelligence”, now in its sixth edition, was started ten years ago, with the organization of ANTS’98. As some readers might recall, the ?rst edition of ANTS was titled “ANTS’98 – From Ant Colonies to Arti?cial Ants: First International Workshop on Ant Colony Op- mization. ” In fact, at that time the focus was mainly on ant colony optimization (ACO), the ?rst swarm intelligence algorithm to go beyond a pure scienti?c interest and to enter the realm of real-world applications. Interestingly, in the ten years after the ?rst edition there has been a gr- ing interest not only for ACO, but for a number of other studies that belong more generally to the area of swarmintelligence. The rapid growth of the swarm intelligence ?eld is attested by a number of indicators. First, the number of s- missions and participants to the ANTS conferences has steadily increased over the years. Second, a number of international conferences in computational - telligence and related disciplines organize workshops on subjects such as swarm intelligence, ant algorithms, ant colony optimization, and particle swarm op- mization. Third, IEEE startedorganizing,in 2003,the IEEE SwarmIntelligence Symposium (in order to maintain unity in this growing ?eld, we are currently establishingacooperationagreementbetweenIEEE SISandANTSsoastohave 1 IEEE SIS in odd years and ANTS in even years). Last, the Swarm Intelligence journal was born.

Author : Vasant, Pandian M.
Publisher : IGI Global
ISBN 13 : 1466620870
Total Pages : 735 pages
Book Rating : 4.72/5 ( download)

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Download or read book Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance written by Vasant, Pandian M. and published by IGI Global. This book was released on 2012-09-30 with total page 735 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization techniques have developed into a significant area concerning industrial, economics, business, and financial systems. With the development of engineering and financial systems, modern optimization has played an important role in service-centered operations and as such has attracted more attention to this field. Meta-heuristic hybrid optimization is a newly development mathematical framework based optimization technique. Designed by logicians, engineers, analysts, and many more, this technique aims to study the complexity of algorithms and problems. Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance explores the emerging study of meta-heuristics optimization algorithms and methods and their role in innovated real world practical applications. This book is a collection of research on the areas of meta-heuristics optimization algorithms in engineering, business, economics, and finance and aims to be a comprehensive reference for decision makers, managers, engineers, researchers, scientists, financiers, and economists as well as industrialists.

Author : Ildar Batyrshin
Publisher : Springer
ISBN 13 : 364225330X
Total Pages : 556 pages
Book Rating : 4.00/5 ( download)

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Download or read book Advances in Soft Computing written by Ildar Batyrshin and published by Springer. This book was released on 2011-11-22 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 7094 and 7095 constitutes the refereed proceedings of the 10th Mexican International Conference on Artificial Intelligence, MICAI 2011, held in Puebla, Mexico, in November/December 2011. The 96 revised papers presented were carefully selected from XXX submissions. The second volume contains 46 papers focusing on soft computing. The papers are organized in the following topical sections: fuzzy logic, uncertainty and probabilistic reasoning; evolutionary algorithms and other naturally-inspired algorithms; data mining; neural networks and hybrid intelligent systems; and computer vision and image processing.

Author : Raghu Nandan Sengupta
Publisher : CRC Press
ISBN 13 : 1351727400
Total Pages : 936 pages
Book Rating : 4.02/5 ( download)

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Download or read book Decision Sciences written by Raghu Nandan Sengupta and published by CRC Press. This book was released on 2016-11-30 with total page 936 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook is an endeavour to cover many current, relevant, and essential topics related to decision sciences in a scientific manner. Using this handbook, graduate students, researchers, as well as practitioners from engineering, statistics, sociology, economics, etc. will find a new and refreshing paradigm shift as to how these topics can be put to use beneficially. Starting from the basics to advanced concepts, authors hope to make the readers well aware of the different theoretical and practical ideas, which are the focus of study in decision sciences nowadays. It includes an excellent bibliography/reference/journal list, information about a variety of datasets, illustrated pseudo-codes, and discussion of future trends in research. Covering topics ranging from optimization, networks and games, multi-objective optimization, inventory theory, statistical methods, artificial neural networks, times series analysis, simulation modeling, decision support system, data envelopment analysis, queueing theory, etc., this reference book is an attempt to make this area more meaningful for varied readers. Noteworthy features of this handbook are in-depth coverage of different topics, solved practical examples, unique datasets for a variety of examples in the areas of decision sciences, in-depth analysis of problems through colored charts, 3D diagrams, and discussions about software.