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Maria Dimakopoulou
Maria Dimakopoulou
Director of Machine Learning & Head of Homepage Personalization, Spotify
Verified email at spotify.com - Homepage
Title
Cited by
Cited by
Year
Estimation considerations in contextual bandits
M Dimakopoulou, Z Zhou, S Athey, G Imbens
arXiv preprint arXiv:1711.07077, 2017
2602017
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
2432019
Doubly robust off-policy evaluation with shrinkage
Y Su, M Dimakopoulou, A Krishnamurthy, M Dudík
International Conference on Machine Learning, 9167-9176, 2020
962020
Coordinated exploration in concurrent reinforcement learning
M Dimakopoulou, B Van Roy
International Conference on Machine Learning, 1271-1279, 2018
472018
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
402021
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
392016
ADMM SLIM: Sparse Recommendations for Many Users
H Steck, M Dimakopoulou, N Riabov, T Jebara
352020
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
302019
Online multi-armed bandits with adaptive inference
M Dimakopoulou, Z Ren, Z Zhou
Advances in Neural Information Processing Systems 34, 1939-1951, 2021
282021
Scalable coordinated exploration in concurrent reinforcement learning
M Dimakopoulou, I Osband, B Van Roy
Advances in Neural Information Processing Systems, 4219-4227, 2018
272018
Marginal Posterior Sampling for Slate Bandits
M Dimakopoulou, N Vlassis, T Jebara
2019 International Joint Conference on Artificial Intelligence, 2019
182019
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
162021
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
82023
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
72021
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
52020
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
42022
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
22022
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
22019
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
12024
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
12022
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