| A continuous-time approach to online optimization J Kwon, P Mertikopoulos Journal of Dynamics and Games 4 (2), 125–148, 2017 | 61 | 2017 |
| Unifying mirror descent and dual averaging A Juditsky, J Kwon, É Moulines Mathematical Programming 199 (1), 793-830, 2023 | 30 | 2023 |
| Gains and losses are fundamentally different in regret minimization: The sparse case J Kwon, V Perchet Journal of Machine Learning Research 17 (227), 1-32, 2016 | 29 | 2016 |
| Sparse Stochastic Bandits J Kwon, V Perchet, C Vernade Proceedings of Machine Learning Research (COLT 2017) 65, 1269–1270, 2017 | 17 | 2017 |
| Online Learning and Blackwell Approachability with Partial Monitoring: Optimal Convergence Rates J Kwon, V Perchet Proceedings of Machine Learning Research (AISTATS 2017) 54, 604-613, 2017 | 13 | 2017 |
| Refined approachability algorithms and application to regret minimization with global costs J Kwon Journal of Machine Learning Research 22 (200), 1-38, 2021 | 4 | 2021 |
| A MOM-based ensemble method for robustness, subsampling and hyperparameter tuning J Kwon, G Lecué, M Lerasle | 3* | 2021 |
| Mirror descent strategies for regret minimization and approachability J Kwon Université Pierre-et-Marie-Curie, 2016 | 3 | 2016 |
| pyPLNmodels: A Python package to analyze multivariate high-dimensional count data B Batardiere, J Kwon, J Chiquet | 1 | 2024 |
| Finite-sum optimization: Adaptivity to smoothness and loopless variance reduction B Batardière, J Kwon arXiv preprint arXiv:2307.12615, 2023 | 1 | 2023 |
| Blackwell's Approachability with Time-Dependent Outcome Functions and Dot Products. Application to the Big Match J Kwon, B Ziliotto arXiv preprint arXiv:2303.04956, 2023 | 1 | 2023 |
| A universal bound on the variations of bounded convex functions J Kwon Journal of Convex Analysis 24 (1), 67--73, 2017 | 1 | 2017 |
| A regret minimization approach to fixed point iterations J Kwon Book of abstracts PGMO DAYS 2024, 74, 2024 | | 2024 |
| pyPLNmodels B Batardière, J Chiquet, J Kwon | | 2024 |
| Importance sampling-based gradient method for dimension reduction in Poisson log-normal model B Batardière, J Chiquet, J Kwon, J Stoehr arXiv preprint arXiv:2410.00476, 2024 | | 2024 |
| A gradient approximation with importance sampling for dimension reduction in natural exponential families B Batardière, J Chiquet, J Kwon, J Stoehr 55èmes journées de Statistiques de la SFdS, 2024 | | 2024 |
| Regret bounds J Kwon | | 2024 |
| Benchmarking predictive models: evaluating parametric, ensemble, and deep learning approaches for animal phenotype prediction from genotypes. E Barrey, B Hanczar, J Chiquet, D Boichard, JG de Herve, A Ricard, ... AI and biology Symposium, 2024 | | 2024 |
| A collection of Poisson lognormal models for multivariate analysis of count data J Chiquet, M Mariadassou, S Robin, B Batardière, J Kwon | | |
| Poisson lognormal models for count data J Chiquet, M Mariadassou, S Robin, B Batardière, J Kwon, J Stoehr | | |
Vianney PerchetCrest, ENSAE & Criteo AI LabAdresse e-mail validée de normalesup.org