| Non-asymptotic Analysis of Biased Stochastic Approximation Scheme B Karimi, B Miasojedow, É Moulines, HT Wai 32nd Conference on Learning Theory (COLT), 2019, 2019 | 118 | 2019 |
| On the global convergence of (fast) incremental expectation maximization methods B Karimi, HT Wai, É Moulines, M Lavielle Advances in Neural Information Processing Systems (NeurIPS), 2019, 2833-2843, 2019 | 42 | 2019 |
| Fedsketch: Communication-efficient and private federated learning via sketching F Haddadpour, B Karimi, P Li, X Li arXiv preprint arXiv:2008.04975, 2020 | 28 | 2020 |
| Joint learning of object graph and relation graph for visual question answering H Li, X Li, B Karimi, J Chen, M Sun IEEE International Conference on Multimedia & Expo (ICME), 2022, 2022 | 25 | 2022 |
| On Distributed Adaptive Optimization with Gradient Compression X Li, B Karimi, P Li International Conference on Learning Representations (ICLR), 2022, 2022 | 25 | 2022 |
| Towards Better Generalization of Adaptive Gradient Methods Y Zhou, B Karimi, J Yu, Z Xu, P Li Advances in Neural Information Processing Systems (NeurIPS), 2020, 810--821, 2020 | 23 | 2020 |
| On the convergence of decentralized adaptive gradient methods X Chen, B Karimi, W Zhao, P Li 14th Asian Conference on Machine Learning (ACML), 2022, 217-232, 2023 | 21 | 2023 |
| f-SAEM: A fast Stochastic Approximation of the EM algorithm for nonlinear mixed effects models B Karimi, M Lavielle, E Moulines Computational Statistics & Data Analysis (CSDA) 141, 123-138, 2020 | 8 | 2020 |
| An Optimistic Acceleration of AMSGrad for Nonconvex Optimization JK Wang, X Li, B Karimi, P Li 13th Asian Conference on Machine Learning (ACML), 2021, 422-437, 2021 | 6 | 2021 |
| On the Convergence Properties of the Mini-Batch EM and MCEM Algorithms B Karimi, M Lavielle, É Moulines HAL preprint hal: 02334485, 2019 | 6 | 2019 |
| Variational Flow Graphical Model S Ren, B Karimi, D Li, P Li The 28th Conference on Knowledge Discovery and Data Mining (KDD), ACM 2022, 2022 | 4 | 2022 |
| Minimization by Incremental Stochastic Surrogate Optimization for Large Scale Nonconvex Problems B Karimi, HT Wai, E Moulines, P Li International Conference on Algorithmic Learning Theory (ALT), 606-637, 2022 | 4 | 2022 |
| Layerwise and dimensionwise locally adaptive optimization algorithm B Karimi, X Li, PL Fed-lamb arXiv preprint arXiv:2110.00532, 2021 | 4 | 2021 |
| Layer-wise and dimension-wise locally adaptive federated learning B Karimi, P Li, X Li arXiv preprint arXiv:2110.00532, 2021 | 3 | 2021 |
| A doubly stochastic surrogate optimization scheme for non-convex finite-sum problems B Karimi, HT Wai, E Moulines 1st Symposium on Advances in Approximate Bayesian Inference (AABI), 2018, 2019 | 3 | 2019 |
| Efficient Metropolis-Hastings sampling for nonlinear mixed effects models B Karimi, M Lavielle International Conference on Bayesian Statistics in Action (BAYSM 2018), 85-93, 2018 | 3 | 2018 |
| FeatureBox: Feature Engineering on GPUs for Massive-Scale Ads Systems W Zhao, X Jiao, X Luo, J Li, B Karimi, P Li IEEE International Conference on Big Data (IEEE BigData), 2022, 2022 | 2 | 2022 |
| Fed-LAMB: layer-wise and dimension-wise locally adaptive federated learning B Karimi, P Li, X Li 39th Conference on Uncertainty in Artificial Intelligence (UAI 2023), 1037-1046, 2023 | 1 | 2023 |
| Two-Timescale Stochastic EM Algorithms B Karimi, P Li IEEE International Symposium on Information Theory (ISIT), 2021, 2021 | 1 | 2021 |
| Fed-LAMB: Layerwise and dimensionwise locally adaptive optimization algorithm B Karimi, X Li, P Li arXiv preprint arXiv:2110.00532, 2021 | 1 | 2021 |
Eric MoulinesProfesseur, Ecole Polytechnique, Membre de l'Académie des Sciencesยืนยันอีเมลแล้วที่ polytechnique.edu