Advancements in Knowledge Distillation: Towards New Horizons of Intelligent Systems / Studies in Computational Intelligence Bd.1100 (PDF)
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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.
- 2023, 1st ed. 2023, 232 Seiten, Englisch
- Herausgegeben: Witold Pedrycz, Shyi-Ming Chen
- Verlag: Springer Nature Switzerland
- ISBN-10: 3031320956
- ISBN-13: 9783031320958
- Erscheinungsdatum: 13.06.2023
Abhängig von Bildschirmgrösse und eingestellter Schriftgrösse kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Grösse: 7.80 MB
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