Optimal importance sampling for federated learning E Rizk, S Vlaski, AH Sayed ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 21 | 2021 |
Federated learning under importance sampling E Rizk, S Vlaski, AH Sayed IEEE Transactions on Signal Processing 70, 5381-5396, 2022 | 16 | 2022 |
A graph federated architecture with privacy preserving learning E Rizk, AH Sayed 2021 IEEE 22nd International Workshop on Signal Processing Advances in …, 2021 | 10 | 2021 |
Second-order guarantees in federated learning S Vlaski, E Rizk, AH Sayed 2020 54th Asilomar Conference on Signals, Systems, and Computers, 915-922, 2020 | 4 | 2020 |
Tracking performance of online stochastic learners S Vlaski, E Rizk, AH Sayed IEEE Signal Processing Letters 27, 1385-1389, 2020 | 2 | 2020 |
Network Classifiers With Output Smoothing E Rizk, R Nassif, AH Sayed arXiv preprint arXiv:1911.04870, 2019 | 1 | 2019 |
Multi-Agent Adversarial Training Using Diffusion Learning Y Cao, E Rizk, S Vlaski, AH Sayed arXiv preprint arXiv:2303.01936, 2023 | | 2023 |
Enforcing Privacy in Distributed Learning with Performance Guarantees E Rizk, S Vlaski, AH Sayed arXiv preprint arXiv:2301.06412, 2023 | | 2023 |
Decentralized Semi-supervised Learning over Multitask Graphs M Issa, R Nassif, E Rizk, AH Sayed 2022 56th Asilomar Conference on Signals, Systems, and Computers, 419-425, 2022 | | 2022 |
Local Graph-homomorphic Processing for Privatized Distributed Systems E Rizk, S Vlaski, AH Sayed arXiv preprint arXiv:2210.15414, 2022 | | 2022 |
Privatized Graph Federated Learning E Rizk, S Vlaski, AH Sayed arXiv preprint arXiv:2203.07105, 2022 | | 2022 |
Dynamic Federated Learning E Rizk, S Vlaski, AH Sayed International Workshop on Signal Processing Advances in Wireless …, 2020 | | 2020 |
On the entropy of some classes of distributions and their mixtures EA Rizk | | 2020 |
ASL SA Alghunaim, V Bordignon, H Cai, Y Cao, LCE Cassano, S Deschamps, ... | | |