The non-stationary stochastic multi-armed bandit problem

Author:

Allesiardo RobinORCID,Féraud Raphaël,Maillard Odalric-Ambrym

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computational Theory and Mathematics,Computer Science Applications,Modelling and Simulation,Information Systems

Reference18 articles.

1. Allesiardo, R., Féraud, R.: EXP3 with drift detection for the switching bandit problem. In: 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA 2015)

2. Auer, P., Cesa-Bianchi, N., Fischer, P.: Finite-time analysis of the multiarmed bandit problem. Mach. Learn. 47(2–3), 235–256 (2002a)

3. Auer, P., Cesa-Bianchi, N., Freund, Y., Schapire, R.E.: The nonstochastic multiarmed bandit problem. SIAM J. Comput. 32(1), 48–77 (2002b)

4. Bubeck, S., Cesa-Bianchi, N.: Regret analysis of stochastic and nonstochastic multi-armed bandit problems. In: Foundations and Trends in Machine Learning. (2012) http://dblp.uni-trier.de/rec/bibtex/journals/ftml/BubeckC12

5. Bubeck, S., Slivkins, A.: The best of both worlds: stochastic and adversarial bandits. In: COLT 2012—the 25th Annual Conference on Learning Theory, pp. 42.1–42.23. Edinburgh, Scotland, 25–27 June 2012

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