Clément Calauzènes
Clément Calauzènes
Criteo AI Lab
Verified email at criteo.com
Title
Cited by
Cited by
Year
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
782018
On the (non-) existence of convex, calibrated surrogate losses for ranking
C Calauzenes, N Usunier, P Gallinari
Advances in Neural Information Processing Systems 25, 197-205, 2012
442012
Learning scoring functions with order-preserving losses and standardized supervision
D Buffoni, C Calauzenes, P Gallinari, N Usunier
ICML, 2011
342011
Fairness-aware learning for continuous attributes and treatments
J Mary, C Calauzènes, N El Karoui
International Conference on Machine Learning, 4382-4391, 2019
172019
Thresholding the virtual value: a simple method to increase welfare and lower reserve prices in online auction systems
T Nedelec, M Abeille, C Calauzenes, N El Karoui, B Heymann, V Perchet
arXiv preprint arXiv:1808.06979, 2018
62018
Distributed SAGA: Maintaining linear convergence rate with limited communication
C Calauzenes, NL Roux
arXiv preprint arXiv:1705.10405, 2017
62017
Explicit shading strategies for repeated truthful auctions
M Abeille, C Calauzènes, NE Karoui, T Nedelec, V Perchet
arXiv preprint arXiv:1805.00256, 2018
52018
Calibration and regret bounds for order-preserving surrogate losses in learning to rank
C Calauzènes, N Usunier, P Gallinari
Machine learning 93 (2-3), 227-260, 2013
52013
Improved Optimistic Algorithms for Logistic Bandits
L Faury, M Abeille, C Calauzènes, O Fercoq
International Conference on Machine Learning, 2020
42020
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
22019
Improving Evolutionary Strategies with Generative Neural Networks
L Faury, C Calauzenes, O Fercoq, S Krichen
arXiv preprint arXiv:1901.11271, 2019
22019
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
12019
Thresholding at the monopoly price: an agnostic way to improve bidding strategies in revenue-maximizing auctions
T Nedelec, M Abeille, C Calauzènes, B Heymann, V Perchet, N El Karoui
arXiv, arXiv: 1808.06979, 2018
12018
Wasserstein Learning of Determinantal Point Processes
L Anquetil, M Gartrell, A Rakotomamonjy, U Tanielian, C Calauzènes
arXiv preprint arXiv:2011.09712, 2020
2020
Learning in repeated auctions
T Nedelec, C Calauzènes, NE Karoui, V Perchet
arXiv preprint arXiv:2011.09365, 2020
2020
Instance-Wise Minimax-Optimal Algorithms for Logistic Bandits
M Abeille, L Faury, C Calauzènes
arXiv preprint arXiv:2010.12642, 2020
2020
Do Not Mask What You Do Not Need to Mask: a Parser-Free Virtual Try-On
T Issenhuth, J Mary, C Calauzènes
arXiv preprint arXiv:2007.02721, 2020
2020
Robust Stackelberg buyers in repeated auctions
T Nedelec, C Calauzenes, V Perchet, N El Karoui
International Conference on Artificial Intelligence and Statistics, 1342-1351, 2020
2020
On ranking via sorting by estimated expected utility
C Calauzènes, N Usunier
Advances in Neural Information Processing Systems 33, 2020
2020
Real-Time Optimisation for Online Learning in Auctions
L Croissant, M Abeille, C Calauzenes
International Conference on Machine Learning, 2020
2020
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