Introduces fundamental theory, basic and advanced algorithms, and system design issues. Essential for researchers and developers.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Song Guo is a Full Professor in the Department of Computing at The Hong Kong Polytechnic University. He is an IEEE Fellow and the Editor-in-Chief of the IEEE Open Journal of the Computer Society. He was a member of the IEEE ComSoc Board of Governors and a Distinguished Lecturer of the IEEE Communications Society.
Zhihao Qu is an assistant researcher in the School of Computer and Information at Hohai University and in the Department of Computing at The Hong Kong Polytechnic University.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Hardcover. Etat : new. Hardcover. Discover this multi-disciplinary and insightful work, which integrates machine learning, edge computing, and big data. Presents the basics of training machine learning models, key challenges and issues, as well as comprehensive techniques including edge learning algorithms, and system design issues. Describes architectures, frameworks, and key technologies for learning performance, security, and privacy, as well as incentive issues in training/inference at the network edge. Intended to stimulate fruitful discussions, inspire further research ideas, and inform readers from both academia and industry backgrounds. Essential reading for experienced researchers and developers, or for those who are just entering the field. Introduces fundamental theory, basic and advanced algorithms, and system design issues. Essential reading for experienced researchers and developers, or for those who are just entering the field. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781108832373
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