| Estimation considerations in contextual bandits M Dimakopoulou, Z Zhou, S Athey, G Imbens arXiv preprint arXiv:1711.07077, 2017 | 239 | 2017 |
| Balanced linear contextual bandits M Dimakopoulou, Z Zhou, S Athey, G Imbens Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3445-3453, 2019 | 217 | 2019 |
| Doubly robust off-policy evaluation with shrinkage Y Su, M Dimakopoulou, A Krishnamurthy, M Dudík International Conference on Machine Learning, 9167-9176, 2020 | 106 | 2020 |
| Coordinated exploration in concurrent reinforcement learning M Dimakopoulou, B Van Roy International Conference on Machine Learning, 1271-1279, 2018 | 48 | 2018 |
| Post-contextual-bandit inference A Bibaut, M Dimakopoulou, N Kallus, A Chambaz, M van der Laan Advances in Neural Information Processing Systems 34, 28548-28559, 2021 | 47 | 2021 |
| ADMM SLIM: Sparse Recommendations for Many Users H Steck, M Dimakopoulou, N Riabov, T Jebara | 42 | 2020 |
| Reliable and efficient performance monitoring in linux M Dimakopoulou, S Eranian, N Koziris, N Bambos SC'16: Proceedings of the International Conference for High Performance …, 2016 | 42 | 2016 |
| Online multi-armed bandits with adaptive inference M Dimakopoulou, Z Ren, Z Zhou Advances in Neural Information Processing Systems 34, 1939-1951, 2021 | 34 | 2021 |
| On the Design of Estimators for Bandit Off-Policy Evaluation N Vlassis, A Bibaut, M Dimakopoulou, T Jebara International Conference on Machine Learning, 6468-6476, 2019 | 32 | 2019 |
| Scalable coordinated exploration in concurrent reinforcement learning M Dimakopoulou, I Osband, B Van Roy Advances in Neural Information Processing Systems, 4219-4227, 2018 | 27 | 2018 |
| Marginal Posterior Sampling for Slate Bandits M Dimakopoulou, N Vlassis, T Jebara 2019 International Joint Conference on Artificial Intelligence, 2019 | 18 | 2019 |
| Risk minimization from adaptively collected data: Guarantees for supervised and policy learning A Bibaut, N Kallus, M Dimakopoulou, A Chambaz, M van der Laan Advances in Neural Information Processing Systems 34, 19261-19273, 2021 | 17 | 2021 |
| Calibrated recommendations as a minimum-cost flow problem H Abdollahpouri, Z Nazari, A Gain, C Gibson, M Dimakopoulou, ... Proceedings of the Sixteenth ACM International Conference on Web Search and …, 2023 | 11 | 2023 |
| Sequential causal inference in a single world of connected units A Bibaut, M Petersen, N Vlassis, M Dimakopoulou, M van der Laan arXiv preprint arXiv:2101.07380, 2021 | 8 | 2021 |
| Reveal 2020: Bandit and reinforcement learning from user interactions T Joachims, Y Raimond, O Koch, M Dimakopoulou, F Vasile, ... Proceedings of the 14th ACM Conference on Recommender Systems, 628-629, 2020 | 5 | 2020 |
| Society of Agents: Regret Bounds of Concurrent Thompson Sampling Y Chen, P Dong, Q Bai, M Dimakopoulou, W Xu, Z Zhou Advances in Neural Information Processing Systems 35, 7587-7598, 2022 | 4 | 2022 |
| Evaluating the Surrogate Index as a Decision-Making Tool Using 200 A/B Tests at Netflix V Zhang, M Zhao, M Dimakopoulou, A Le, N Kallus arXiv preprint arXiv:2311.11922, 2024 | 3 | 2024 |
| MORS 2022: The Second Workshop on Multi-Objective Recommender Systems H Abdollahpouri, S Sahebi, M Elahi, M Mansoury, B Loni, Z Nazari, ... Proceedings of the 16th ACM Conference on Recommender Systems, 658-660, 2022 | 3 | 2022 |
| REVEAL 2022: Reinforcement Learning-Based Recommender Systems at Scale R Liaw, P Bailey, Y Li, M Dimakopoulou, Y Raimond Proceedings of the 16th ACM Conference on Recommender Systems, 684-685, 2022 | 3 | 2022 |
| REVEAL 2019: closing the loop with the real world: reinforcement and robust estimators for recommendation T Joachims, M Dimakopoulou, A Swaminathan, Y Raimond, O Koch, ... Proceedings of the 13th ACM Conference on Recommender Systems, 568-569, 2019 | 2 | 2019 |
guido imbensStanford UniversityVerified email at stanford.edu
