| Statistical optimality of stochastic gradient descent on hard learning problems through multiple passes L Pillaud-Vivien, A Rudi, F Bach Advances in Neural Information Processing Systems 31, 2018 | 70 | 2018 |
| Implicit bias of sgd for diagonal linear networks: a provable benefit of stochasticity S Pesme, L Pillaud-Vivien, N Flammarion Advances in Neural Information Processing Systems 34, 29218-29230, 2021 | 30 | 2021 |
| Exponential convergence of testing error for stochastic gradient methods L Pillaud-Vivien, A Rudi, F Bach Conference On Learning Theory, 250-296, 2018 | 24 | 2018 |
| Last iterate convergence of SGD for Least-Squares in the Interpolation regime. AV Varre, L Pillaud-Vivien, N Flammarion Advances in Neural Information Processing Systems 34, 21581-21591, 2021 | 15 | 2021 |
| Statistical estimation of the poincaré constant and application to sampling multimodal distributions L Pillaud-Vivien, F Bach, T Lelièvre, A Rudi, G Stoltz International Conference on Artificial Intelligence and Statistics, 2753-2763, 2020 | 10 | 2020 |
| Central Limit Theorem for stationary Fleming--Viot particle systems in finite spaces T Lelievre, L Pillaud-Vivien, J Reygner ALEA, Lat. Am. J. Probab. Math. Stat. 15, 1163–1182, 2018 | 10 | 2018 |
| Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs E Boursier, L Pillaud-Vivien, N Flammarion arXiv preprint arXiv:2206.00939, 2022 | 5 | 2022 |
| Overcoming the curse of dimensionality with Laplacian regularization in semi-supervised learning V Cabannes, L Pillaud-Vivien, F Bach, A Rudi Advances in Neural Information Processing Systems 34, 2021 | 5 | 2021 |
| Label noise (stochastic) gradient descent implicitly solves the Lasso for quadratic parametrisation LP Vivien, J Reygner, N Flammarion Conference on Learning Theory, 2127-2159, 2022 | 4 | 2022 |
| SGD with large step sizes learns sparse features M Andriushchenko, A Varre, L Pillaud-Vivien, N Flammarion arXiv preprint arXiv:2210.05337, 2022 | 2 | 2022 |
| Learning with reproducing kernel Hilbert spaces: stochastic gradient descent and laplacian estimation L Pillaud-Vivien Université Paris sciences et lettres, 2020 | 1 | 2020 |
| La Résilience à Paris: états des lieux et préconisations multi-bénéfices pour l’espace public A Hatchuel, A Labourdette, F Leduc, L Pillaud-Vivien, M Renaudin Mairie de Paris, 2017 | | 2017 |
Alessandro RudiINRIA - École Normale SupérieureVerified email at inria.fr
