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First Order Stochastic Optimization Methods by Lan Guanghui (33 results)
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First-Order and Stochastic Optimization Methods for Machine Learning
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First-order and Stochastic Optimization Methods for Machine Learning
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First-order and Stochastic Optimization Methods for Machine Learning (Springer Series in the Data Sciences)
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First-order and Stochastic Optimization Methods for Machine Learning (Springer Series in the Data Sciences)
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First-order and Stochastic Optimization Methods for Machine Learning
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First-Order and Stochastic Optimization Methods for Machine Learning
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First-order and Stochastic Optimization Methods for Machine Learning
Published by Springer Nature Switzerland AG, CH, 2021
ISBN 10: 3030395707 ISBN 13: 9783030395704
Language: English
£ 77.91
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Add to basketPaperback. Condition: New. 2020 ed. 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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First-order and Stochastic Optimization Methods for Machine Learning
Published by Springer Nature Switzerland AG, CH, 2020
ISBN 10: 3030395677 ISBN 13: 9783030395674
Language: English
£ 91.82
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Add to basketHardback. Condition: New. 2020 ed. 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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First-order and Stochastic Optimization Methods for Machine Learning
Published by Springer Nature Switzerland AG, CH, 2021
ISBN 10: 3030395707 ISBN 13: 9783030395704
Language: English
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
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£ 90.14
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Add to basketPaperback. Condition: New. 2020 ed. 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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First-order and Stochastic Optimization Methods for Machine Learning
Published by Springer Nature Switzerland AG, CH, 2020
ISBN 10: 3030395677 ISBN 13: 9783030395674
Language: English
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 4 out of 5 stars
£ 106.02
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Add to basketHardback. Condition: New. 2020 ed. 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: New. New. book.
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First-order and Stochastic Optimization Methods for Machine Learning
Published by Springer International Publishing, Springer International Publishing, 2021
ISBN 10: 3030395707 ISBN 13: 9783030395704
Language: English
£ 133.71
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Add to basketTaschenbuch. 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.
-
First-order and Stochastic Optimization Methods for Machine Learning
Published by Springer International Publishing, 2020
ISBN 10: 3030395677 ISBN 13: 9783030395674
Language: English
£ 133.71
Convert currency£ 12.13 shipping from Germany to United KingdomQuantity: 1 available
Add to basketBuch. 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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Hardcover. Condition: Brand New. 582 pages. 9.25x6.50x1.50 inches. In Stock.
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First-order and Stochastic Optimization Methods for Machine Learning
Published by Springer International Publishing Mai 2021, 2021
ISBN 10: 3030395707 ISBN 13: 9783030395704
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
£ 62.08
Convert currency£ 9.53 shipping from Germany to United KingdomQuantity: 2 available
Add to basketTaschenbuch. 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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First-order and Stochastic Optimization Methods for Machine Learning
Published by Springer International Publishing Mai 2020, 2020
ISBN 10: 3030395677 ISBN 13: 9783030395674
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
£ 62.08
Convert currency£ 9.53 shipping from Germany to United KingdomQuantity: 2 available
Add to basketBuch. 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. This item is printed on demand.
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First-order and Stochastic Optimization Methods for Machine Learning
Published by Springer International Publishing, 2021
ISBN 10: 3030395707 ISBN 13: 9783030395704
Language: English
£ 113.73
Convert currency£ 21.66 shipping from Germany to United KingdomQuantity: Over 20 available
Add to basketCondition: 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 .
