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Advancements in Knowledge Distillation: Towards New Horizons of Intelligent Systems - Shyi-Ming Chen - Bog

Bag om Advancements in Knowledge Distillation: Towards New Horizons of Intelligent Systems

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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  • Sprog:
  • Engelsk
  • ISBN:
  • 9783031320941
  • Indbinding:
  • Hardback
  • Sideantal:
  • 244
  • Udgivet:
  • 14. juni 2023
  • Udgave:
  • 23001
  • Størrelse:
  • 160x19x241 mm.
  • Vægt:
  • 535 g.
  • 8-11 hverdage.
  • 10. december 2024
På lager

Normalpris

  • BLACK WEEK

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Prøv i 30 dage for 45 kr.
Herefter fra 79 kr./md. Ingen binding.

Beskrivelse af Advancements in Knowledge Distillation: Towards New Horizons of Intelligent Systems

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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