Open Access
Issue
ITM Web Conf.
Volume 80, 2025
2025 2nd International Conference on Advanced Computer Applications and Artificial Intelligence (ACAAI 2025)
Article Number 02004
Number of page(s) 13
Section Reinforcement Learning, Bandits & Optimization
DOI https://doi.org/10.1051/itmconf/20258002004
Published online 16 December 2025
  1. T. Lattimore, C. Szepesvári, Bandit Algorithms (Cambridge University Press, Cambridge, U.K., 2020) [Google Scholar]
  2. P. Auer, N. Cesa-Bianchi, P. Fischer, Finite-time analysis of the multiarmed bandit problem. Mach. Learn. 47, 235–256 (2002) [CrossRef] [Google Scholar]
  3. D.J. Russo, B. Van Roy, A. Kazerouni, I. Osband, Z. Wen, A tutorial on Thompson sampling. Found. Trends Mach. Learn. 11, 1–96 (2018) [CrossRef] [Google Scholar]
  4. S. Bubeck, N. Cesa-Bianchi, Regret analysis of stochastic and nonstochastic multi- armed bandit problems. Found. Trends Mach. Learn. 5, 1–122 (2012) [Google Scholar]
  5. O. Chapelle, L. Li, An empirical evaluation of Thompson sampling, in Adv. Neural Inf. Process. Syst. (NeurIPS, 2011), pp. 2249–2257 [Google Scholar]
  6. B.P.G. Van Parys, N. Golrezaei, Optimal learning for structured bandits. Optim. Online (2020). https://optimization-online.org/2020/02/7618/ [Google Scholar]
  7. Y. Abbasi-Yadkori, D. Pál, C. Szepesvári, Improved algorithms for linear stochastic bandits. J. Mach. Learn. Res. 12, 1627–1676 (2011) [Google Scholar]
  8. Retail Rocket, E-commerce dataset (Kaggle, 2016). https://www.kaggle.com/datasets/retailrocket/ecommerce-dataset [Google Scholar]
  9. L. Li, W. Chu, J. Langford, R.E. Schapire, A contextual-bandit approach to personalized news article recommendation, in Proc. 19th Int. Conf. World Wide Web (WWW, 2010), pp. 661–670 [Google Scholar]
  10. J. Vermorel, M. Mohri, Multi-armed bandit algorithms and empirical evaluation. Mach. Learn. 66, 151–176 (2007) [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.