Advancements in Knowledge Distillation: Towards New Horizons of Intelligent Systems (1st ed. 2023)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Studies in Computational Intelligence, 1100
Release date:	June 2023
First published:	2023
Editors:	Witold Pedrycz • Shyi-Ming Chen
Dimensions:	235 x 155mm (L x W)
Pages:	232
Edition:	1st ed. 2023
ISBN-13:	978-3-03-132094-1
Categories:	Books
LSN:	3-03-132094-8
Barcode:	9783031320941

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