Online Learning and Bandits
Multi-armed bandits, contextual bandits, and best-arm identification.
Online Learning and Bandits. Multi-armed bandits, contextual bandits, and best-arm identification.
Foundations and canonical references
The standard treatments of online learning and bandits approach the subject from complementary angles. Cesa, Prediction, Learning, and Games (2006) is the anchor reference for the subject and lays out the core definitions, theorems, and worked examples that practitioners return to. Hazan, Introduction to Online Convex Optimization (2016) gives a parallel, more proof-oriented exposition of the same material and is widely used as a graduate text.
Open methodological questions for online learning and bandits include sharpening the bridges between foundational theory and computational practice, extending classical results to broader or more structured settings, and integrating the techniques surveyed above with adjacent mathematical disciplines. The references listed in this page are the entry points that current work builds on.
Prerequisites
Sources
- textbook · primary · 2006Prediction, Learning, and Gamescesa-bianchi-2006, lugosi-2006
- textbook · primary · 2016Introduction to Online Convex Optimizationhazan-2016
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