| Multitask learning over graphs: An approach for distributed, streaming machine learning R Nassif, S Vlaski, C Richard, J Chen, AH Sayed IEEE Signal Processing Magazine 37 (3), 14-25, 2020 | 97 | 2020 |
| Multitask diffusion adaptation over asynchronous networks R Nassif, C Richard, A Ferrari, AH Sayed IEEE Transactions on Signal Processing 64 (11), 2835-2850, 2016 | 71 | 2016 |
| Proximal multitask learning over networks with sparsity-inducing coregularization R Nassif, C Richard, A Ferrari, AH Sayed IEEE Transactions on Signal Processing 64 (23), 6329-6344, 2016 | 70 | 2016 |
| Diffusion LMS for multitask problems with local linear equality constraints R Nassif, C Richard, A Ferrari, AH Sayed IEEE Transactions on Signal Processing 65 (19), 4979-4993, 2017 | 66 | 2017 |
| Distributed diffusion adaptation over graph signals R Nassif, C Richard, J Chen, AH Sayed 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 56 | 2018 |
| Online distributed learning over graphs with multitask graph-filter models F Hua, R Nassif, C Richard, H Wang, AH Sayed IEEE Transactions on Signal and Information Processing over Networks 6, 63-77, 2020 | 39 | 2020 |
| Online graph learning from sequential data S Vlaski, HP Maretić, R Nassif, P Frossard, AH Sayed 2018 IEEE Data Science Workshop (DSW), 190-194, 2018 | 36 | 2018 |
| Diffusion LMS over multitask networks with noisy links R Nassif, C Richard, J Chen, A Ferrari, AH Sayed 2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016 | 35 | 2016 |
| Diffusion LMS with communication delays: Stability and performance analysis F Hua, R Nassif, C Richard, H Wang, AH Sayed IEEE Signal Processing Letters 27, 730-734, 2020 | 31 | 2020 |
| Learning over Multitask Graphs-Part I: Stability Analysis R Nassif, S Vlaski, C Richard, AH Sayed IEEE Open Journal of Signal Processing, 2020 | 30 | 2020 |
| Adaptation and Learning Over Networks Under Subspace Constraints—Part I: Stability Analysis R Nassif, S Vlaski, AH Sayed IEEE Transactions on Signal Processing 68, 1346-1360, 2020 | 29 | 2020 |
| A graph diffusion LMS strategy for adaptive graph signal processing R Nassif, C Richard, J Chen, AH Sayed 2017 51st Asilomar Conference on Signals, Systems, and Computers, 1973-1976, 2017 | 27 | 2017 |
| Multitask diffusion LMS with sparsity-based regularization R Nassif, C Richard, A Ferrari, AH Sayed 2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015 | 27 | 2015 |
| A preconditioned graph diffusion LMS for adaptive graph signal processing F Hua, R Nassif, C Richard, H Wang, AH Sayed 2018 26th European Signal Processing Conference (EUSIPCO), 111-115, 2018 | 24 | 2018 |
| A regularization framework for learning over multitask graphs R Nassif, S Vlaski, C Richard, AH Sayed IEEE Signal Processing Letters 26 (2), 297-301, 2018 | 20 | 2018 |
| Quantization for Decentralized Learning Under Subspace Constraints R Nassif, S Vlaski, M Carpentiero, V Matta, M Antonini, AH Sayed IEEE Transactions on Signal Processing 71, 2320-2335, 2023 | 19 | 2023 |
| Adaptation and learning over networks under subspace constraints—Part II: Performance analysis R Nassif, S Vlaski, AH Sayed IEEE Transactions on Signal Processing 68, 2948-2962, 2020 | 18 | 2020 |
| Distributed inference over networks under subspace constraints R Nassif, S Vlaski, AH Sayed ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 13 | 2019 |
| Learning over Multitask Graphs-Part II: Performance Analysis R Nassif, S Vlaski, C Richard, AH Sayed IEEE Open Journal of Signal Processing, 2020 | 12 | 2020 |
| Penalty-based multitask estimation with non-local linear equality constraints F Hua, R Nassif, C Richard, H Wang 2017 IEEE 7th International Workshop on Computational Advances in Multi …, 2017 | 9 | 2017 |
Ali H SayedDean of Engineering, EPFL, SwitzerlandVerified email at epfl.ch
