Bandit Convex Optimisation - Couverture rigide

Lattimore, Tor

Couverture rigide

ISBN 10 : 1009607596 ISBN 13 : 9781009607599

Editeur : Cambridge University Press, 2026

Synopsis

This comprehensive reference brings readers to the frontier of research on bandit convex optimization or zeroth-order convex optimization. The focus is on theoretical aspects, with short, self-contained chapters covering all the necessary tools from convex optimization and online learning, including gradient-based algorithms, interior point methods, cutting plane methods and information-theoretic machinery. The book features a large number of exercises, open problems and pointers to future research directions, making it ideal for students as well as researchers.

A propos du livre

À propos de l'auteur

Tor Lattimore is a researcher at Google DeepMind working on reinforcement learning, bandits, optimisation and the theory of machine learning. He is the co-author of an introductory book on bandit algorithms and has published nearly 100 conference and journal articles. He is an action editor for the Journal of Machine Learning Research.

Détails de l'édition

• Éditeur: Cambridge University Press
• Date d'édition: 2026
• Langue: anglais
• ISBN 10: 1009607596
• ISBN 13: 9781009607599
• Reliure: Relié
• Nombre de pages: 280
• Coordonnées du fabricant: Cambridge University Press; https://www.cambridge.org/; ; Via Honduras,15; Pomezia; Italia; 71; Italie