Order Total (1 Item Items):
Shipping Destination:
First Order Stochastic Optimization Methods by Lan Guanghui (34 results)
Skip to main search results
Search filters
Product Type
- All Product Types
- Books (34)
- Magazines & Periodicals (No further results match this refinement)
- Comics (No further results match this refinement)
- Sheet Music (No further results match this refinement)
- Art, Prints & Posters (No further results match this refinement)
- Photographs (No further results match this refinement)
- Maps (No further results match this refinement)
- Manuscripts & Paper Collectibles (No further results match this refinement)
Condition Learn more
- New (30)
- As New, Fine or Near Fine (4)
- Very Good or Good (No further results match this refinement)
- Fair or Poor (No further results match this refinement)
- As Described (No further results match this refinement)
Binding
Collectible Attributes
- First Edition (No further results match this refinement)
- Signed (No further results match this refinement)
- Dust Jacket (No further results match this refinement)
- Seller-Supplied Images (21)
- Not Print on Demand (26)
Language (1)
Free Shipping
Seller Location
Seller Rating
-
Condition: As New. Unread book in perfect condition.
-
Condition: As New. Unread book in perfect condition.
-
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
£ 61.30
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
-
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
£ 61.30
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
-
-
-
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.
-
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.
-
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. 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
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.
-
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.
-
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, 2020
ISBN 10: 3030395677 ISBN 13: 9783030395674
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Hardback. 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.
-
-
Brand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
-
-
-
-
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. 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
Book 5 of 11: Springer Series in the Data SciencesLanguage: English
Published by Springer Nature Switzerland AG, CH, 2020
ISBN 10: 3030395677 ISBN 13: 9783030395674
Hardback. 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.
-
-
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.
-
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, 2020
ISBN 10: 3030395677 ISBN 13: 9783030395674
Buch. 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.
-
Paperback. Condition: Brand New. 595 pages. 9.25x6.10x1.21 inches. In Stock.
-
Hardcover. Condition: Brand New. 582 pages. 9.25x6.50x1.50 inches. In Stock.
-
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.
-
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 2020, 2020
ISBN 10: 3030395677 ISBN 13: 9783030395674
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Buch. 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.
-
Condition: New. This item is printed on demand.
-
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 .
