| Grace: A compressed communication framework for distributed machine learning H Xu, CY Ho, AM Abdelmoniem, A Dutta, EH Bergou, K Karatsenidis, ... 2021 IEEE 41st international conference on distributed computing systems …, 2021 | 103 | 2021 |
| On the discrepancy between the theoretical analysis and practical implementations of compressed communication for distributed deep learning A Dutta, EH Bergou, AM Abdelmoniem, CY Ho, AN Sahu, M Canini, ... Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3817-3824, 2020 | 100 | 2020 |
| Compressed communication for distributed deep learning: Survey and quantitative evaluation H Xu, CY Ho, AM Abdelmoniem, A Dutta, EH Bergou, K Karatsenidis, ... | 92 | 2020 |
| Convergence and complexity analysis of a Levenberg–Marquardt algorithm for inverse problems EH Bergou, Y Diouane, V Kungurtsev Journal of Optimization Theory and Applications 185, 927-944, 2020 | 81 | 2020 |
| Stochastic three points method for unconstrained smooth minimization EH Bergou, E Gorbunov, P Richtarik SIAM Journal on Optimization 30 (4), 2726-2749, 2020 | 59 | 2020 |
| Levenberg--Marquardt methods based on probabilistic gradient models and inexact subproblem solution, with application to data assimilation E Bergou, S Gratton, LN Vicente SIAM/ASA Journal on Uncertainty Quantification 4 (1), 924-951, 2016 | 48 | 2016 |
| Stochastic sign descent methods: New algorithms and better theory M Safaryan, P Richtárik International Conference on Machine Learning, 9224-9234, 2021 | 46 | 2021 |
| A stochastic derivative free optimization method with momentum E Gorbunov, A Bibi, O Sener, EH Bergou, P Richtárik arXiv preprint arXiv:1905.13278, 2019 | 33 | 2019 |
| Hybrid Levenberg–Marquardt and weak-constraint ensemble Kalman smoother method J Mandel, E Bergou, S Gürol, S Gratton, I Kasanický Nonlinear Processes in Geophysics 23 (2), 59-73, 2016 | 30 | 2016 |
| A subsampling line-search method with second-order results EH Bergou, Y Diouane, V Kunc, V Kungurtsev, CW Royer INFORMS Journal on Optimization 4 (4), 403-425, 2022 | 29 | 2022 |
| On the use of the energy norm in trust-region and adaptive cubic regularization subproblems E Bergou, Y Diouane, S Gratton Computational Optimization and Applications 68, 533-554, 2017 | 28 | 2017 |
| A Stochastic Levenberg--Marquardt Method Using Random Models with Complexity Results EH Bergou, Y Diouane, V Kungurtsev, CW Royer SIAM/ASA Journal on Uncertainty Quantification 10 (1), 507-536, 2022 | 23* | 2022 |
| On the convergence of a non-linear ensemble Kalman smoother EH Bergou, S Gratton, J Mandel Applied Numerical Mathematics 137, 151-168, 2019 | 18 | 2019 |
| Client selection in federated learning based on gradients importance O Marnissi, HE Hammouti, EH Bergou AIP Conference Proceedings 3034 (1), 2024 | 15 | 2024 |
| A stochastic derivative-free optimization method with importance sampling: Theory and learning to control A Bibi, EH Bergou, O Sener, B Ghanem, P Richtarik Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3275-3282, 2020 | 14 | 2020 |
| A line-search algorithm inspired by the adaptive cubic regularization framework and complexity analysis EH Bergou, Y Diouane, S Gratton Journal of Optimization Theory and Applications 178, 885-913, 2018 | 13 | 2018 |
| The exact condition number of the truncated singular value solution of a linear ill-posed problem EH Bergou, S Gratton, J Tshimanga SIAM Journal on Matrix Analysis and Applications 35 (3), 1073-1085, 2014 | 12 | 2014 |
| 4DVAR by ensemble Kalman smoother J Mandel, E Bergou, S Gratton arXiv preprint arXiv:1304.5271, 2013 | 11 | 2013 |
| Age-of-updates optimization for UAV-assisted networks MN Ndiaye, EH Bergou, M Ghogho, H El Hammouti GLOBECOM 2022-2022 IEEE Global Communications Conference, 450-455, 2022 | 10 | 2022 |
| Personalized federated learning with communication compression EH Bergou, K Burlachenko, A Dutta, P Richtárik arXiv preprint arXiv:2209.05148, 2022 | 10 | 2022 |