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9783030395704 - First-order and Stochastic Optimization Methods for Machine Learning Springer Series in the Data Sciences by Lan, Guanghui (19 results)
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Condition: As New. Unread book in perfect condition.
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First-order and Stochastic Optimization Methods for Machine Learning
Book 5 of 11: Springer Series in the Data SciencesLanguage: English
Published by Springer Nature Switzerland AG, CH, 2021
ISBN 10: 3030395707 ISBN 13: 9783030395704
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: New. 2020 ed.
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First-order and Stochastic Optimization Methods for Machine Learning (Springer Series in the Data Sciences)
Book 5 of 11: Springer Series in the Data SciencesSeller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 62.62
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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First-order and Stochastic Optimization Methods for Machine Learning
Book 5 of 11: Springer Series in the Data SciencesSeller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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First-order and Stochastic Optimization Methods for Machine Learning
Book 5 of 11: Springer Series in the Data SciencesSeller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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First-order and Stochastic Optimization Methods for Machine Learning
Book 5 of 11: Springer Series in the Data SciencesLanguage: English
Published by Springer Nature Switzerland AG, CH, 2021
ISBN 10: 3030395707 ISBN 13: 9783030395704
Paperback. Condition: New. 2020 ed.
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First-order And Stochastic Optimization
Book 5 of 11: Springer Series in the Data SciencesSeller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
Condition: New.
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Taschenbuch. Condition: Neu. First-order and Stochastic Optimization Methods for Machine Learning | Guanghui Lan | Taschenbuch | Springer Series in the Data Sciences | xiii | Englisch | 2021 | Springer | EAN 9783030395704 | 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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First-order and Stochastic Optimization Methods for Machine Learning
Book 5 of 11: Springer Series in the Data SciencesLanguage: English
Published by Springer International Publishing, Springer International Publishing, 2021
ISBN 10: 3030395707 ISBN 13: 9783030395704
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms. In spite of the intensive research and development in this area, there does not exist a systematic treatment to introduce the fundamental concepts and recent progresses on machine learning algorithms, especially on those based on stochastic optimization methods, randomized algorithms, nonconvex optimization, distributed and online learning, and projection free methods. This book will benefit the broad audience in the area of machine learning, artificial intelligence and mathematical programming community by presenting these recent developments in a tutorial style, starting from the basic building blocks to the most carefully designed and complicated algorithms for machine learning.
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Paperback. Condition: Brand New. 595 pages. 9.25x6.10x1.21 inches. In Stock.
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First-order and Stochastic Optimization Methods for Machine Learning
Book 5 of 11: Springer Series in the Data SciencesLanguage: English
Published by Springer International Publishing Mai 2021, 2021
ISBN 10: 3030395707 ISBN 13: 9783030395704
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms. In spite of the intensive research and development in this area, there does not exist a systematic treatment to introduce the fundamental concepts and recent progresses on machine learning algorithms, especially on those based on stochastic optimization methods, randomized algorithms, nonconvex optimization, distributed and online learning, and projection free methods. This book will benefit the broad audience in the area of machine learning, artificial intelligence and mathematical programming community by presenting these recent developments in a tutorial style, starting from the basic building blocks to the most carefully designed and complicated algorithms for machine learning. 596 pp. Englisch.
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Condition: new. Questo è un articolo print on demand.
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First-order and Stochastic Optimization Methods for Machine Learning
Book 5 of 11: Springer Series in the Data SciencesLanguage: English
Published by Springer International Publishing, 2021
ISBN 10: 3030395707 ISBN 13: 9783030395704
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents comprehensive study of topics in machine learning from introductory material through most complicated algorithmsSummarizes most recent findings in the area of machine learningAddresses a broad audience .
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Condition: New. Print on Demand This item is printed on demand.
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First-order and Stochastic Optimization Methods for Machine Learning
Book 5 of 11: Springer Series in the Data SciencesLanguage: English
Published by Springer, Palgrave Macmillan Mai 2021, 2021
ISBN 10: 3030395707 ISBN 13: 9783030395704
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms. In spite of the intensive research and development in this area, there does not exist a systematic treatment to introduce the fundamental concepts and recent progresses on machine learning algorithms, especially on those based on stochastic optimization methods, randomized algorithms, nonconvex optimization, distributed and online learning, and projection free methods. This book will benefit the broad audience in the area of machine learning, artificial intelligence and mathematical programming community by presenting these recent developments in a tutorial style, starting from the basic building blocks to the most carefully designed and complicated algorithms for machine learning.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 596 pp. Englisch.
