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- Vol. 4 Issue 3
- Article
Optimization of Ads Using Reinforcement Learning and Comparison of Algorithms
Authors
2Asst. Professor, Department of Mechatronics, Dr. Mahalingam College of Engineering and Technology, Pollachi,Tamilnadu, India. 134 Department of Mechatronics, Dr. Mahalingam College of Engineering and Technology, Pollachi, Tamilnadu, India.
Article Information
- Published In
- Volume 4, Issue 3 (2023)
- Published Online
- May-June 2023
- Pages
- 115-118
- Article Type
- Research Article
- Check for updates
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References
[1]. Kuleshov, V., &Precup, D. (2014). Algorithms for multi-armed bandit problems. Journal of Machine Learning Research, 15(1), 95-
127.
[2]. Lattimore, T., &Szepesvári, C. (2020). Bandit algorithms (Vol. 1). Cambridge University Press
[3]. Chapelle, O., & Li, L. (2011). An empirical evaluation of Thompson sampling. In Advances in neural information processing systems
(pp. 2249-2257).
[4]. May, A., &Korda, N. (2012). Thompson sampling for 1-dimensional exponential families with unknown variance. In Advances in
Neural Information Processing Systems (pp. 3034-3042).
[5]. Russo, D. (2016). A Tutorial on Thompson Sampling. Foundations and Trends® in Machine Learning, 9(4-5), 338-403
127.
[2]. Lattimore, T., &Szepesvári, C. (2020). Bandit algorithms (Vol. 1). Cambridge University Press
[3]. Chapelle, O., & Li, L. (2011). An empirical evaluation of Thompson sampling. In Advances in neural information processing systems
(pp. 2249-2257).
[4]. May, A., &Korda, N. (2012). Thompson sampling for 1-dimensional exponential families with unknown variance. In Advances in
Neural Information Processing Systems (pp. 3034-3042).
[5]. Russo, D. (2016). A Tutorial on Thompson Sampling. Foundations and Trends® in Machine Learning, 9(4-5), 338-403
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