Federated and Transfer Learning
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- Hardcover
- Taschenbuch ausgewählt
- eBook
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Sprache:Englisch
Fr. 201.00
inkl. gesetzl. MwSt.,
Beschreibung
Produktdetails
Einband
Taschenbuch
Erscheinungsdatum
02.10.2023
Abbildungen
VIII, 371 p. 90 illus., 80 illus. in color.
Herausgeber
Roozbeh Razavi-Far + weitereVerlag
SpringerSeitenzahl
371
Maße (L/B/H)
23.5/15.5/2.1 cm
Gewicht
575 g
Auflage
1st ed. 2023
Sprache
Englisch
ISBN
978-3-031-11750-3
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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