| Maximum mean discrepancy gradient flow M Arbel, A Korba, A Salim, A Gretton Advances in Neural Information Processing Systems 32, 2019 | 105 | 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, 4672-4682, 2020 | 58 | 2020 |
| Optimal and practical algorithms for smooth and strongly convex decentralized optimization D Kovalev, A Salim, P Richtárik Advances in Neural Information Processing Systems 33, 18342-18352, 2020 | 57 | 2020 |
| Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions S Chen, S Chewi, J Li, Y Li, A Salim, AR Zhang The Eleventh International Conference on Learning Representations, 2022 | 52 | 2022 |
| Towards a theory of non-log-concave sampling: first-order stationarity guarantees for langevin monte carlo K Balasubramanian, S Chewi, MA Erdogdu, A Salim, S Zhang Conference on Learning Theory, 2896-2923, 2022 | 32 | 2022 |
| The Wasserstein proximal gradient algorithm A Salim, A Korba, G Luise Advances in Neural Information Processing Systems 33, 12356-12366, 2020 | 32 | 2020 |
| Primal dual interpretation of the proximal stochastic gradient Langevin algorithm A Salim, P Richtárik Advances in Neural Information Processing Systems 33, 3786-3796, 2020 | 28 | 2020 |
| Textbooks Are All You Need S Gunasekar, Y Zhang, J Aneja, CCT Mendes, A Del Giorno, S Gopi, ... arXiv preprint arXiv:2306.11644, 2023 | 27 | 2023 |
| Dualize, split, randomize: Toward fast nonsmooth optimization algorithms A Salim, L Condat, K Mishchenko, P Richtárik Journal of Optimization Theory and Applications 195 (1), 102-130, 2022 | 27 | 2022 |
| A constant step Forward-Backward algorithm involving random maximal monotone operators P Bianchi, W Hachem, A Salim Journal of Convex Analysis 26 (2), 387-436, 2019 | 27 | 2019 |
| Improved analysis for a proximal algorithm for sampling Y Chen, S Chewi, A Salim, A Wibisono Conference on Learning Theory, 2984-3014, 2022 | 26 | 2022 |
| Distributed fixed point methods with compressed iterates S Chraibi, A Khaled, D Kovalev, P Richtárik, A Salim, M Takáč arXiv preprint arXiv:1912.09925, 2019 | 23 | 2019 |
| Snake: a stochastic proximal gradient algorithm for regularized problems over large graphs A Salim, P Bianchi, W Hachem IEEE Transactions on Automatic Control 64 (5), 1832-1847, 2019 | 21 | 2019 |
| Stochastic proximal langevin algorithm: Potential splitting and nonasymptotic rates A Salim, D Kovalev, P Richtárik Advances in Neural Information Processing Systems 32, 2019 | 19 | 2019 |
| An optimal algorithm for strongly convex minimization under affine constraints A Salim, L Condat, D Kovalev, P Richtárik International Conference on Artificial Intelligence and Statistics, 4482-4498, 2022 | 17 | 2022 |
| Constant step stochastic approximations involving differential inclusions: stability, long-run convergence and applications P Bianchi, W Hachem, A Salim Stochastics 91 (2), 288-320, 2019 | 17* | 2019 |
| A convergence theory for SVGD in the population limit under Talagrand’s inequality T1 A Salim, L Sun, P Richtarik International Conference on Machine Learning, 19139-19152, 2022 | 12* | 2022 |
| The probability flow ODE is provably fast S Chen, S Chewi, H Lee, Y Li, J Lu, A Salim Advances in Neural Information Processing Systems 36, 2023 | 8 | 2023 |
| A stochastic proximal point algorithm for total variation regularization over large scale graphs A Salim, P Bianchi, W Hachem, J Jakubowicz 2016 IEEE 55th Conference on Decision and Control (CDC), 4490-4495, 2016 | 7 | 2016 |
| A fully stochastic primal-dual algorithm P Bianchi, W Hachem, A Salim Optimization Letters 15 (2), 701-710, 2021 | 6* | 2021 |
Pascal BianchiTélécom ParisTechПотвърден имейл адрес: telecom-paristech.fr
