| Acceleration methods A d’Aspremont, D Scieur, A Taylor Foundations and Trends in Optimization 5 (1-2), 1-245, 2021 | 236 | 2021 |
| Regularized nonlinear acceleration D Scieur, A d'Aspremont, F Bach Advances In Neural Information Processing Systems 29, 2016 | 181 | 2016 |
| Application of stochastic dual dynamic programming to the real-time dispatch of storage under renewable supply uncertainty A Papavasiliou, Y Mou, L Cambier, D Scieur IEEE Transactions on Sustainable Energy 9 (2), 547-558, 2017 | 165 | 2017 |
| Integration methods and optimization algorithms D Scieur, V Roulet, F Bach, A d'Aspremont Advances in Neural Information Processing Systems 30, 2017 | 131 | 2017 |
| Accelerating smooth games by manipulating spectral shapes W Azizian, D Scieur, I Mitliagkas, S Lacoste-Julien, G Gidel International Conference on Artificial Intelligence and Statistics, 1705-1715, 2020 | 64 | 2020 |
| Acceleration through spectral density estimation F Pedregosa, D Scieur International Conference on Machine Learning, 7553-7562, 2020 | 55 | 2020 |
| Universal average-case optimality of Polyak momentum D Scieur, F Pedregosa International conference on machine learning, 8565-8572, 2020 | 47 | 2020 |
| Nonlinear acceleration of stochastic algorithms D Scieur, A d'Aspremont, F Bach Advances in Neural Information Processing Systems 30, 2017 | 46 | 2017 |
| Super-acceleration with cyclical step-sizes B Goujaud, D Scieur, A Dieuleveut, AB Taylor, F Pedregosa International Conference on Artificial Intelligence and Statistics, 3028-3065, 2022 | 44 | 2022 |
| Online Regularized Nonlinear Acceleration D Scieur, E Oyallon, A d'Aspremont, F Bach arXiv preprint arXiv:1805.09639, 2018 | 40* | 2018 |
| Nonlinear acceleration of momentum and primal-dual algorithms R Bollapragada, D Scieur, A d'Aspremont Mathematical Programming, 2022 | 34* | 2022 |
| The curse of unrolling: Rate of differentiating through optimization D Scieur, G Gidel, Q Bertrand, F Pedregosa Advances in Neural Information Processing Systems 35, 17133-17145, 2022 | 22 | 2022 |
| Affine invariant analysis of frank-wolfe on strongly convex sets T Kerdreux, L Liu, S Lacoste-Julien, D Scieur International conference on machine learning, 5398-5408, 2021 | 19 | 2021 |
| Extra-gradient with player sampling for faster convergence in n-player games S Jelassi, C Domingo-Enrich, D Scieur, A Mensch, J Bruna International Conference on Machine Learning, 4736-4745, 2020 | 18* | 2020 |
| Only tails matter: Average-case universality and robustness in the convex regime L Cunha, G Gidel, F Pedregosa, D Scieur, C Paquette International Conference on Machine Learning, 4474-4491, 2022 | 14 | 2022 |
| Adaptive Quasi-Newton and anderson acceleration framework with explicit global (accelerated) convergence rates D Scieur International Conference on Artificial Intelligence and Statistics, 883-891, 2024 | 12 | 2024 |
| Average-case acceleration for bilinear games and normal matrices C Domingo-Enrich, F Pedregosa, D Scieur International Conference on Learning Representations, 2020 | 10 | 2020 |
| Generalization of Quasi-Newton methods: application to robust symmetric multisecant updates D Scieur, L Liu, T Pumir, N Boumal International Conference on Artificial Intelligence and Statistics, 550-558, 2021 | 9 | 2021 |
| Acceleration in optimization D Scieur Université Paris sciences et lettres, 2018 | 8 | 2018 |
| Generalized framework for nonlinear acceleration D Scieur arXiv preprint arXiv:1903.08764, 2019 | 7 | 2019 |
Alexandre d'AspremontCNRS & Ecole Normale Supérieure, ParisVerified email at di.ens.fr
