Librería: SpringBooks, Berlin, Alemania
Original o primera edición
EUR 27,56
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Añadir al carritoHardcover. Condición: Very Good. 1. Auflage. unread, some shelfwear.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 154,08
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 154,08
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Publicado por Springer Nature Singapore, Springer Nature Singapore, 2020
ISBN 10: 9811529094 ISBN 13: 9789811529092
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 164,49
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Añadir al carritoBuch. Condición: 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.
Publicado por Springer Nature Singapore, 2021
ISBN 10: 9811529124 ISBN 13: 9789811529122
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 165,03
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Añadir al carritoTaschenbuch. Condición: 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.
Librería: California Books, Miami, FL, Estados Unidos de America
EUR 194,49
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Librería: California Books, Miami, FL, Estados Unidos de America
EUR 194,49
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Publicado por Springer Nature Singapore, Springer Nature Singapore Mai 2020, 2020
ISBN 10: 9811529094 ISBN 13: 9789811529092
Idioma: Inglés
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 160,49
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Añadir al carritoBuch. Condición: Neu. Neuware -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 the algorithms 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 300 pp. Englisch.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 193,14
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Añadir al carritoCondición: New. 1st ed. 2020 edition NO-PA16APR2015-KAP.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 193,40
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Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 157,82
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Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
EUR 158,22
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EUR 204,54
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Añadir al carritoHardcover. Condición: New. New. book.
Publicado por Springer-Nature New York Inc, 2021
ISBN 10: 9811529124 ISBN 13: 9789811529122
Idioma: Inglés
Librería: Revaluation Books, Exeter, Reino Unido
EUR 231,70
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Añadir al carritoPaperback. Condición: Brand New. 299 pages. 9.25x6.10x0.63 inches. In Stock.
Publicado por Springer-Nature New York Inc, 2020
ISBN 10: 9811529094 ISBN 13: 9789811529092
Idioma: Inglés
Librería: Revaluation Books, Exeter, Reino Unido
EUR 234,20
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Añadir al carritoHardcover. Condición: Brand New. 275 pages. 9.75x6.50x0.75 inches. In Stock.
Publicado por Machinery Industry Press, 2021
ISBN 10: 7111685008 ISBN 13: 9787111685005
Idioma: Chino
Librería: liu xing, Nanjing, JS, China
EUR 125,47
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Añadir al carritopaperback. Condición: New. Paperback. Pub Date: 2021-07-01 Pages: 264 Language: Chinese Publisher: Machinery Industry Press. Machine learning is a discipline about building predictive or descriptive models from data to improve machine problem-solving capabilities.?After the model is established. an appropriate optimization algorithm is needed to solve the parameters of the model. Therefore. the optimization algorithm is an important part of machine learning.?However. traditional optimization algorithms are not complete.
Librería: moluna, Greven, Alemania
EUR 136,16
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The first monograph on accelerated first-order optimization algorithms used in machine learningIncludes forewords by Michael I. Jordan, Zongben Xu, and Zhi-Quan Luo, and written by experts on machine learning and optimization.
Publicado por Springer, Berlin|Springer Nature Singapore|Springer, 2021
ISBN 10: 9811529124 ISBN 13: 9789811529122
Idioma: Inglés
Librería: moluna, Greven, Alemania
EUR 137,26
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 opt.
Publicado por Springer Nature Singapore Mai 2021, 2021
ISBN 10: 9811529124 ISBN 13: 9789811529122
Idioma: Inglés
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 160,49
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 275 pp. Englisch.
Publicado por Springer Nature Singapore Mai 2020, 2020
ISBN 10: 9811529094 ISBN 13: 9789811529092
Idioma: Inglés
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 160,49
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 300 pp. Englisch.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 203,31
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Librería: Majestic Books, Hounslow, Reino Unido
EUR 204,00
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 207,87
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 208,57
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