| Offline a/b testing for recommender systems A Gilotte, C Calauzčnes, T Nedelec, A Abraham, S Dollé Proceedings of the Eleventh ACM International Conference on Web Search and …, 2018 | 218 | 2018 |
| Learning from Bandit Feedback: An Overview of the State-of-the-art O Jeunen, D Mykhaylov, D Rohde, F Vasile, A Gilotte, M Bompaire arXiv preprint arXiv:1909.08471, 2019 | 15 | 2019 |
| Causal models for real time bidding with repeated user interactions M Bompaire, A Gilotte, B Heymann Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 10 | 2021 |
| Fast offline policy optimization for large scale recommendation O Sakhi, D Rohde, A Gilotte Proceedings of the AAAI Conference on Artificial Intelligence 37 (8), 9686-9694, 2023 | 2 | 2023 |
| Lessons from the AdKDD’21 Privacy-Preserving ML Challenge E Diemert, R Fabre, A Gilotte, F Jia, B Leparmentier, J Mary, Z Qu, ... Proceedings of the ACM Web Conference 2022, 2026-2035, 2022 | 2 | 2022 |
| Learning a logistic model from aggregated data A Gilotte, D Rohde AdKDD Workshop, 2021 | 2 | 2021 |
| Repeated Bidding with Dynamic Value B Heymann, A Gilotte, R Chan-Renous arXiv preprint arXiv:2308.01755, 2023 | | 2023 |
| Learning from aggregated data with a maximum entropy model A Gilotte, AB Yahmed, D Rohde arXiv preprint arXiv:2210.02450, 2022 | | 2022 |
| Generation of incremental bidding and recommendations for electronic advertisements C Calauzčnes, C Renaudin, A Gilotte, E Diemert US Patent 11,049,150, 2021 | | 2021 |
| Ranking metrics on non-shuffled traffic A Gilotte arXiv preprint arXiv:1909.07926, 2019 | | 2019 |
