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Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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Condition: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
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Brand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
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Condition: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.
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Federated and Transfer Learning (Hardcover)
Language: English
Published by Springer International Publishing AG, Cham, 2022
ISBN 10: 3031117476 ISBN 13: 9783031117473
First Edition
Hardcover. Condition: new. Hardcover. This book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive factors of federated learning as well as its connection with transfer learning and reinforcement learning. Over the last few years, the machine learning community has become fascinated by federated and transfer learning. Transfer and federated learning have achieved great success and popularity in many different fields of application. The intended audience of this book is students and academics aiming to apply federated and transfer learning to solve different kinds of real-world problems, as well as scientists, researchers, and practitioners in AI industries, autonomous vehicles, and cyber-physical systems who wish to pursue new scientific innovations and update their knowledge on federated and transfer learning and their applications. This book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive factors of federated learning as well as its connection with transfer learning and reinforcement learning. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Generative Adversarial Learning: Architectures and Applications (Intelligent Systems Reference Library, 217)
Book 182 of 188: Intelligent Systems Reference LibraryUS$ 174.03
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Condition: Hervorragend. Zustand: Hervorragend | Seiten: 380 | Sprache: Englisch | Produktart: Bücher | This book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive factors of federated learning as well as its connection with transfer learning and reinforcement learning. Over the last few years, the machine learning community has become fascinated by federated and transfer learning. Transfer and federated learning have achieved great success and popularity in many different fields of application. The intended audience of this book is students and academics aiming to apply federated and transfer learning to solve different kinds of real-world problems, as well as scientists, researchers, and practitioners in AI industries, autonomous vehicles, and cyber-physical systems who wish to pursue new scientific innovations and update their knowledge on federated and transfer learning and their applications.
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Federated and Transfer Learning (Adaptation, Learning, and Optimization, 27)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Federated and Transfer Learning (Adaptation, Learning, and Optimization)
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Federated and Transfer Learning
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Federated and Transfer Learning (Paperback)
Language: English
Published by Springer International Publishing AG, Cham, 2023
ISBN 10: 3031117506 ISBN 13: 9783031117503
First Edition
Paperback. Condition: new. Paperback. This book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive factors of federated learning as well as its connection with transfer learning and reinforcement learning. Over the last few years, the machine learning community has become fascinated by federated and transfer learning. Transfer and federated learning have achieved great success and popularity in many different fields of application. The intended audience of this book is students and academics aiming to apply federated and transfer learning to solve different kinds of real-world problems, as well as scientists, researchers, and practitioners in AI industries, autonomous vehicles, and cyber-physical systems who wish to pursue new scientific innovations and update their knowledge on federated and transfer learning and their applications. This book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive factors of federated learning as well as its connection with transfer learning and reinforcement learning. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Federated and Transfer Learning
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
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Condition: As New. Unread book in perfect condition.
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Condition: As New. Unread book in perfect condition.
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Generative Adversarial Learning: Architectures and Applications (Intelligent Systems Reference Library)
Book 182 of 188: Intelligent Systems Reference LibrarySeller: Ria Christie Collections, Uxbridge, United Kingdom
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Generative Adversarial Learning: Architectures and Applications (Intelligent Systems Reference Library, 217)
Book 182 of 188: Intelligent Systems Reference LibrarySeller: Ria Christie Collections, Uxbridge, United Kingdom
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Federated and Transfer Learning
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Federated and Transfer Learning
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Generative Adversarial Learning : Architectures and Applications
Book 182 of 188: Intelligent Systems Reference LibrarySeller: GreatBookPricesUK, Woodford Green, United Kingdom
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Generative Adversarial Learning: Architectures and Applications (Paperback)
Book 182 of 188: Intelligent Systems Reference LibraryLanguage: English
Published by Springer Nature Switzerland AG, Cham, 2023
ISBN 10: 3030913929 ISBN 13: 9783030913922
Paperback. Condition: new. Paperback. This book provides a collection of recent research works addressing theoretical issues on improving the learning process and the generalization of GANs as well as state-of-the-art applications of GANs to various domains of real life. Adversarial learning fascinates the attention of machine learning communities across the world in recent years. Generative adversarial networks (GANs), as the main method of adversarial learning, achieve great success and popularity by exploiting a minimax learning concept, in which two networks compete with each other during the learning process. Their key capability is to generate new data and replicate available data distributions, which are needed in many practical applications, particularly in computer vision and signal processing. The book is intended for academics, practitioners, and research students in artificial intelligence looking to stay up to date with the latest advancements on GANs theoretical developments and their applications. This book provides a collection of recent research works addressing theoretical issues on improving the learning process and the generalization of GANs as well as state-of-the-art applications of GANs to various domains of real life. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
