Computational learning theory

Rubriek: Textual/Printed/Reference Materials - Boek

Prijs: € 54.99

Rating: 0/5

☆

☆

☆

☆

☆

Verzending:
2 - 3 weken

This is a self contained volume in which the authors concentrate on the 'probably approximately correct model'. It will therefore form an introduction to the theory of computational learning, suitable for a broad spectrum of graduate students from theoretical computer science and mathematics.



Computational learning theory is a subject which has been advancing rapidly in the last few years. The authors concentrate on the probably approximately correct model of learning, and gradually develop the ideas of efficiency considerations. Finally, applications of the theory to artificial neural networks are considered. Many exercises are included throughout, and the list of references is extensive. This volume is relatively self contained as the necessary background material from logic, probability and complexity theory is included. It will therefore form an introduction to the theory of computational learning, suitable for a broad spectrum of graduate students from theoretical computer science and mathematics.

• 1 Bekijk alle specificaties

Taal: en

Bindwijze: Paperback

Oorspronkelijke releasedatum: 27 februari 1997

Aantal pagina's: 172

Illustraties: Met illustraties

Hoofdauteur: M. H. G. Anthony

Tweede Auteur: Norman L. Biggs

Co Auteur: Martin Anthony

Hoofduitgeverij: Cambridge University Press

Editie: New edition

Extra groot lettertype: Nee

Product breedte: 170 mm

Product hoogte: 9 mm

Product lengte: 244 mm

Verpakking breedte: 170 mm

Verpakking hoogte: 13 mm

Verpakking lengte: 244 mm

Verpakkingsgewicht: 290 g

EAN: 9780521599221

---