Offline a/b testing for recommender systems A Gilotte, C Calauzènes, T Nedelec, A Abraham, S Dollé Proceedings of the Eleventh ACM International Conference on Web Search and …, 2018 | 238 | 2018 |
Fairness-aware learning for continuous attributes and treatments J Mary, C Calauzenes, N El Karoui International Conference on Machine Learning, 4382-4391, 2019 | 144 | 2019 |
Do Not Mask What You Do Not Need to Mask: a Parser-Free Virtual Try-On T Issenhuth, J Mary, C Calauzènes European Conference on Computer Vision (ECCV), 2020 | 113 | 2020 |
Improved Optimistic Algorithms for Logistic Bandits L Faury, M Abeille, C Calauzènes, O Fercoq International Conference on Machine Learning, 2020 | 95 | 2020 |
On the (non-) existence of convex, calibrated surrogate losses for ranking C Calauzenes, N Usunier, P Gallinari Advances in Neural Information Processing Systems 25, 2012 | 59 | 2012 |
Instance-wise minimax-optimal algorithms for logistic bandits M Abeille, L Faury, C Calauzènes International Conference on Artificial Intelligence and Statistics, 3691-3699, 2021 | 42 | 2021 |
Learning in repeated auctions T Nedelec, C Calauzènes, N El Karoui, V Perchet Foundations and Trends® in Machine Learning 15 (3), 176-334, 2022 | 41 | 2022 |
Learning scoring functions with order-preserving losses and standardized supervision D Buffoni, C Calauzenes, P Gallinari, N Usunier The 28th International Conference on Machine Learning (ICML 2011), 825-832, 2011 | 39 | 2011 |
End-to-end learning of geometric deformations of feature maps for virtual try-on T Issenhuth, J Mary, C Calauzènes arXiv preprint arXiv:1906.01347, 2019 | 25 | 2019 |
Bridging the gap between regret minimization and best arm identification, with application to a/b tests R Degenne, T Nedelec, C Calauzènes, V Perchet The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 24 | 2019 |
Jointly efficient and optimal algorithms for logistic bandits L Faury, M Abeille, KS Jun, C Calauzènes International Conference on Artificial Intelligence and Statistics, 546-580, 2022 | 22 | 2022 |
Regret bounds for generalized linear bandits under parameter drift L Faury, Y Russac, M Abeille, C Calauzènes arXiv preprint arXiv:2103.05750, 2021 | 15 | 2021 |
Distributed SAGA: Maintaining linear convergence rate with limited communication C Calauzenes, NL Roux arXiv preprint arXiv:1705.10405, 2017 | 12 | 2017 |
Pure exploration and regret minimization in matching bandits F Sentenac, J Yi, C Calauzenes, V Perchet, M Vojnovic International Conference on Machine Learning, 9434-9442, 2021 | 9 | 2021 |
Explicit shading strategies for repeated truthful auctions M Abeille, C Calauzènes, NE Karoui, T Nedelec, V Perchet arXiv preprint arXiv:1805.00256, 2018 | 9 | 2018 |
Real-Time Optimisation for Online Learning in Auctions L Croissant, M Abeille, C Calauzenes International Conference on Machine Learning, 2020 | 8 | 2020 |
Improving evolutionary strategies with generative neural networks L Faury, C Calauzenes, O Fercoq, S Krichen arXiv preprint arXiv:1901.11271, 2019 | 8 | 2019 |
Calibration and regret bounds for order-preserving surrogate losses in learning to rank C Calauzènes, N Usunier, P Gallinari Machine learning 93, 227-260, 2013 | 7 | 2013 |
Thresholding the virtual value: a simple method to increase welfare and lower reserve prices in online auction systems T Nedelec, M Abeille, C Calauzènes, N El Karoui, B Heymann, V Perchet arXiv preprint arXiv:1808.06979, 2018 | 6 | 2018 |
On ranking via sorting by estimated expected utility C Calauzènes, N Usunier Advances in Neural Information Processing Systems 33, 3699-3710, 2020 | 5 | 2020 |