2022
Perera, R. M., Oetomo, B., Rubinstein, B. I., & Borovica-Gajic, R. (2022) HMAB: Self-Driving Hierarchy of Bandits for Integrated Physical Database Design Tuning. In: Proceedings of the VLDB Endowment 16.2, pp. 216-229 [publisher link; code; BibTeX]
2021
Perera, R. M., Oetomo, B., Rubinstein, B. I., & Borovica-Gajic, R. (2021). No DBA? No regret! Multi-armed bandits for index tuning of analytical and HTAP workloads with provable guarantees. arXiv preprint arXiv:2108.10130. [BibteX]
Oetomo, B., Perera, R. M., Borovica-Gajic, R., & Rubinstein, B. I. (2021) “Cutting to the Chase with Warm-Start Contextual Bandits”. In: 2021 IEEE 21th International Conference on Data Mining. ICDM. 2021 [BibTeX]
Perera, R. M., Oetomo, B., Rubinstein, B. I., & Borovica-Gajic, R. (2021, April). DBA bandits: Self-driving index tuning under ad-hoc, analytical workloads with safety guarantees. In 2021 IEEE 37th International Conference on Data Engineering (ICDE) (pp. 600-611). IEEE. [BibteX]
2019
Oetomo, B., Perera, M., Borovica-Gajic, R., & Rubinstein, B. I. (2019). A Note on Bounding Regret of the C $^ 2$ UCB Contextual Combinatorial Bandit. arXiv preprint arXiv:1902.07500. [BibteX]