| Maximum mean discrepancy gradient flow M Arbel, A Korba, A Salim, A Gretton Advances in Neural Information Processing Systems 32, 2019 | 114 | 2019 |
| A non-asymptotic analysis for Stein variational gradient descent A Korba, A Salim, M Arbel, G Luise, A Gretton Advances in Neural Information Processing Systems 33, 2020 | 61 | 2020 |
| Proximal causal learning with kernels: Two-stage estimation and moment restriction A Mastouri, Y Zhu, L Gultchin, A Korba, R Silva, MJ Kusner, A Gretton, ... International Conference on Machine Learning, 2021 | 51 | 2021 |
| A learning theory of ranking aggregation A Korba, S Clémençon, E Sibony Artificial Intelligence and Statistics, 1001-1010, 2017 | 41 | 2017 |
| The Wasserstein Proximal Gradient Algorithm A Salim, A Korba, G Luise Advances in Neural Information Processing Systems 33, 2020 | 37 | 2020 |
| A structured prediction approach for label ranking A Korba, A Garcia, FA Buc Advances in Neural Information Processing Systems 31, 2018 | 36 | 2018 |
| Kernel Stein Discrepancy Descent A Korba, PC Aubin-Frankowski, S Majewski, P Ablin International Conference on Machine Learning, 2021 | 24 | 2021 |
| Controlling the distance to a kemeny consensus without computing it Y Jiao, A Korba, E Sibony International Conference on Machine Learning, 2971-2980, 2016 | 17 | 2016 |
| Ranking median regression: Learning to order through local consensus S Clémençon, A Korba, E Sibony Algorithmic Learning Theory, 212-245, 2018 | 15 | 2018 |
| Adaptive Importance Sampling meets Mirror Descent: a Bias-variance tradeoff A Korba, F Portier Artificial Intelligence and Statistics, 2022 | 7 | 2022 |
| Mirror Descent with Relative Smoothness in Measure Spaces, with application to Sinkhorn and EM PC Aubin-Frankowski, A Korba, F Léger Advances in Neural Information Processing Systems 35, 2022 | 6 | 2022 |
| Accurate quantization of measures via interacting particle-based optimization L Xu, A Korba, D Slepcev International Conference on Machine Learning, 24576-24595, 2022 | 5 | 2022 |
| Learning from ranking data: theory and methods A Korba Université Paris-Saclay (ComUE), 2018 | 5 | 2018 |
| Dimensionality reduction and (bucket) ranking: a mass transportation approach M Achab, A Korba, S Clémençon Algorithmic Learning Theory, 64-93, 2019 | 2 | 2019 |
| Exponential Smoothing for Off-Policy Learning I Aouali, VE Brunel, D Rohde, A Korba International Conference on Machine Learning, 2023 | 1 | 2023 |
| Sampling with Mollified Interaction Energy Descent L Li, Q Liu, A Korba, M Yurochkin, J Solomon International Conference on Learning Representations, 2023 | 1 | 2023 |
| Variational Inference of overparameterized Bayesian Neural Networks: a theoretical and empirical study T Huix, S Majewski, A Durmus, E Moulines, A Korba arXiv preprint arXiv:2207.03859, 2022 | 1 | 2022 |
| On aggregation in ranking median regression. S Clémençon, A Korba ESANN, 2018 | 1 | 2018 |
| A connection between Tempering and Entropic Mirror Descent N Chopin, FR Crucinio, A Korba arXiv preprint arXiv:2310.11914, 2023 | | 2023 |
| Multiresolution analysis for the statistical analysis of incomplete rankings S Clémençon, E Sibony, A Korba NIPS 2015-Workshop on Multiresolution Methods for Large Scale Learning, 2015 | | 2015 |
Arthur GrettonGatsby Computational Neuroscience Unit and Google DeepmindVerified email at gatsby.ucl.ac.uk
