The book provides a timely coverage of the paradigm of knowledge distillation-an efficient way of model compression. Knowledge distillation is positioned in a general setting of transfer learning, which effectively learns a lightweight student model from a large teacher model. The book covers a variety of training schemes, teacher-student architectures, and distillation algorithms. The book covers a wealth of topics including recent developments in vision and language learning, relational architectures, multi-task learning, and representative applications to image processing, computer vision, edge intelligence, and autonomous systems. The book is of relevance to a broad audience including researchers and practitioners active in the area of machine learning and pursuing fundamental and applied research in the area of advanced learning paradigms.
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book provides a timely coverage of the paradigm of knowledge distillation-an efficient way ofmodel compression. Knowledge distillation is positioned in a general setting of transfer learning, which effectively learns a lightweight student model from a large teacher model. The book covers a variety of training schemes, teacher-student architectures, and distillation algorithms. The book covers a wealth of topics including recent developments in vision and language learning, relational architectures, multi-task learning, and representative applications to image processing, computer vision, edge intelligence, and autonomous systems. The book is of relevance to a broad audience including researchers and practitioners active in the area of machine learning and pursuing fundamental and applied research in the area of advanced learning paradigms. 244 pp. Englisch. N° de réf. du vendeur 9783031320941
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Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book provides a timely coverage of the paradigm of knowledge distillation-an efficient way of model compression. Knowledge distillation is positioned in a general setting of transfer learning, which effectively learns a lightweight student model from a large teacher model. The book covers a variety of training schemes, teacher-student architectures, and distillation algorithms. The book covers a wealth of topics including recent developments in vision and language learning, relational architectures, multi-task learning, and representative applications to image processing, computer vision, edge intelligence, and autonomous systems. The book is of relevance to a broad audience including researchers and practitioners active in the area of machine learning and pursuing fundamental and applied research in the area of advanced learning paradigms.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 244 pp. Englisch. N° de réf. du vendeur 9783031320941
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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The book provides a timely coverage of the paradigm of knowledge distillation-an efficient way ofmodel compression. Knowledge distillation is positioned in a general setting of transfer learning, which effectively learns a lightweight student model from a large teacher model. The book covers a variety of training schemes, teacher-student architectures, and distillation algorithms. The book covers a wealth of topics including recent developments in vision and language learning, relational architectures, multi-task learning, and representative applications to image processing, computer vision, edge intelligence, and autonomous systems. The book is of relevance to a broad audience including researchers and practitioners active in the area of machine learning and pursuing fundamental and applied research in the area of advanced learning paradigms. N° de réf. du vendeur 9783031320941
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