| Exact diffusion for distributed optimization and learning—Part I: Algorithm development K Yuan, B Ying, X Zhao, AH Sayed IEEE Transactions on Signal Processing 67 (3), 708-723, 2018 | 219 | 2018 |
| Exact diffusion for distributed optimization and learning—Part II: Convergence analysis K Yuan, B Ying, X Zhao, AH Sayed IEEE Transactions on Signal Processing 67 (3), 724-739, 2018 | 93 | 2018 |
| Variance-reduced stochastic learning by networked agents under random reshuffling K Yuan, B Ying, J Liu, AH Sayed IEEE Transactions on Signal Processing 67 (2), 351-366, 2018 | 68 | 2018 |
| Social learning over weakly connected graphs H Salami, B Ying, AH Sayed IEEE Transactions on Signal and Information Processing over Networks 3 (2 …, 2017 | 67 | 2017 |
| Exponential graph is provably efficient for decentralized deep training B Ying, K Yuan, Y Chen, H Hu, P Pan, W Yin Advances in Neural Information Processing Systems 34, 13975-13987, 2021 | 61 | 2021 |
| On the influence of momentum acceleration on online learning K Yuan, B Ying, AH Sayed Journal of Machine Learning Research 17 (192), 1-66, 2016 | 59 | 2016 |
| Supervised learning under distributed features B Ying, K Yuan, AH Sayed IEEE Transactions on Signal Processing 67 (4), 977-992, 2018 | 53 | 2018 |
| On the influence of bias-correction on distributed stochastic optimization K Yuan, SA Alghunaim, B Ying, AH Sayed IEEE Transactions on Signal Processing 68, 4352-4367, 2020 | 48 | 2020 |
| Stochastic learning under random reshuffling with constant step-sizes B Ying, K Yuan, S Vlaski, AH Sayed IEEE Transactions on Signal Processing 67 (2), 474-489, 2018 | 38 | 2018 |
| Stochastic gradient descent with finite samples sizes K Yuan, B Ying, S Vlaski, AH Sayed 2016 IEEE 26th International Workshop on Machine Learning for Signal …, 2016 | 38 | 2016 |
| Variance-reduced stochastic learning under random reshuffling B Ying, K Yuan, AH Sayed IEEE Transactions on Signal Processing 68, 1390-1408, 2020 | 35 | 2020 |
| Information exchange and learning dynamics over weakly connected adaptive networks B Ying, AH Sayed IEEE Transactions on information Theory 62 (3), 1396-1414, 2016 | 27 | 2016 |
| Performance limits of stochastic sub-gradient learning, Part I: Single agent case B Ying, AH Sayed Signal Processing 144, 271-282, 2018 | 25 | 2018 |
| Bluefog: Make decentralized algorithms practical for optimization and deep learning B Ying, K Yuan, H Hu, Y Chen, W Yin arXiv preprint arXiv:2111.04287, 2021 | 22 | 2021 |
| Coordinate-descent diffusion learning by networked agents C Wang, Y Zhang, B Ying, AH Sayed IEEE Transactions on Signal Processing 66 (2), 352-367, 2017 | 21 | 2017 |
| Convergence of variance-reduced stochastic learning under random reshuffling B Ying, K Yuan, AH Sayed arXiv preprint arXiv:1708.01383 2 (3), 6, 2017 | 19 | 2017 |
| On the performance of exact diffusion over adaptive networks K Yuan, SA Alghunaim, B Ying, AH Sayed 2019 IEEE 58th Conference on Decision and Control (CDC), 4898-4903, 2019 | 15 | 2019 |
| Convergence of variance-reduced learning under random reshuffling B Ying, K Yuan, AH Sayed 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 13 | 2018 |
| On the performance of random reshuffling in stochastic learning B Ying, K Yuan, S Vlaski, AH Sayed 2017 Information Theory and Applications Workshop (ITA), 1-5, 2017 | 13 | 2017 |
| Diffusion gradient boosting for networked learning B Ying, AH Sayed 2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 11 | 2017 |
Ali H SayedDean of Engineering, EPFL, SwitzerlandGeverifieerd e-mailadres voor epfl.ch
