Bandit Convex Optimisation

Nyhet

Inbunden, Engelska, 2026

819 kr

Kommande

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.

Produktinformation

Utgivningsdatum2026-02-28
FormatInbunden
SpråkEngelska
Antal sidor277
FörlagCambridge University Press
ISBN9781009607599

Tillhör följande kategorier

Optimering inom Naturvetenskap och teknik
Systemvetenskap och AI inom Data och it

Preface; 1. Introduction and problem statement; 2. Overview of methods and history; 3. Mathematical tools; 4. Bisection in one dimension; 5. Online gradient descent; 6. Self-concordant regularisation; 7. Linear and quadratic bandits; 8. Exponential weights; 9. Cutting plane methods; 10. Online Newton step; 11. Online Newton step for adversarial losses; 12. Gaussian optimistic smoothing; 13. Submodular minimisation; 14. Outlook; Appendix A. Miscellaneous; Appendix B. Concentration; Appendix C. Notation; Bibliography; Index.