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Taschenbuch. Condition: Neu. Machine Learning and Metaheuristics Algorithms, and Applications | First Symposium, SoMMA 2019, Trivandrum, India, December 18-21, 2019, Revised Selected Papers | Sabu M. Thampi (u. a.) | Taschenbuch | xii | Englisch | 2020 | Springer | EAN 9789811543005 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Published by Springer Nature Singapore, Springer Nature Singapore, 2020
ISBN 10: 9811543003 ISBN 13: 9789811543005
Language: English
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the First Symposium onMachine Learning and Metaheuristics Algorithms, and Applications, SoMMA 2019, held inTrivandrum, India, in December 2019.The 17 full papers and 6 short papers presented in this volume were thoroughly reviewed and selected from 53 qualified submissions. The papers cover such topics as machine learning, artificial intelligence, Internet of Things, modeling and simulation, disctibuted computing methodologies, computer graphics, etc.
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ISBN 10: 3031758609 ISBN 13: 9783031758607
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Taschenbuch. Condition: Neu. Machine Learning Algorithms | First International Conference, ICMLA 2024, Himachal Pradesh, India, February 23-24, 2024, Proceedings | Meenu Khurana (u. a.) | Taschenbuch | xxi | Englisch | 2024 | Springer Nature Switzerland | EAN 9783031758607 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Published by Springer International Publishing, Springer Nature Switzerland, 2024
ISBN 10: 3031758609 ISBN 13: 9783031758607
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the First International Conference on Machine Learning Algorithms, ICMLA 2024, held in Himachal Pradesh, India, during February 23-24, 2024.The 23 full papers and 17 short papers included in this book were carefully reviewed and selected from 400 submissions. They were organized in the following topical sections: machine learning; image processing; deep learning.
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Published by Springer Nature Singapore, 2021
ISBN 10: 9811529124 ISBN 13: 9789811529122
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book on optimization includes forewords by Michael I. Jordan, Zongben Xu and Zhi-Quan Luo. Machine learning relies heavily on optimization to solve problems with its learning models, and first-order optimization algorithms are the mainstream approaches. The acceleration of first-order optimization algorithms is crucial for the efficiency of machine learning.Written by leading experts in the field, this book provides a comprehensive introduction to, and state-of-the-art review of accelerated first-order optimization algorithms for machine learning. It discusses a variety of methods, including deterministic and stochastic algorithms, where thealgorithms can be synchronous or asynchronous, for unconstrained and constrained problems, which can be convex or non-convex. Offering a rich blend of ideas, theories and proofs, the book is up-to-date and self-contained. It is an excellent reference resource for users who are seeking faster optimization algorithms, as well asfor graduate students and researchers wanting to grasp the frontiers of optimization in machine learning in a short time.
Published by Springer Nature Singapore, Springer Nature Singapore, 2020
ISBN 10: 9811529094 ISBN 13: 9789811529092
Language: English
Seller: AHA-BUCH GmbH, Einbeck, Germany
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book on optimization includes forewords by Michael I. Jordan, Zongben Xu and Zhi-Quan Luo. Machine learning relies heavily on optimization to solve problems with its learning models, and first-order optimization algorithms are the mainstream approaches. The acceleration of first-order optimization algorithms is crucial for the efficiency of machine learning.Written by leading experts in the field, this book provides a comprehensive introduction to, and state-of-the-art review of accelerated first-order optimization algorithms for machine learning. It discusses a variety of methods, including deterministic and stochastic algorithms, where thealgorithms can be synchronous or asynchronous, for unconstrained and constrained problems, which can be convex or non-convex. Offering a rich blend of ideas, theories and proofs, the book is up-to-date and self-contained. It is an excellent reference resource for users who are seeking faster optimization algorithms, as well asfor graduate students and researchers wanting to grasp the frontiers of optimization in machine learning in a short time.
Published by Springer-Nature New York Inc, 2021
ISBN 10: 9811529124 ISBN 13: 9789811529122
Language: English
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Published by Springer-Nature New York Inc, 2020
ISBN 10: 9811529094 ISBN 13: 9789811529092
Language: English
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Buch. Condition: Neu. Accelerated Optimization for Machine Learning | First-Order Algorithms | Zhouchen Lin (u. a.) | Buch | xxiv | Englisch | 2020 | Springer Singapore | EAN 9789811529092 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
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