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Elsa Rizk
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2020 – today
- 2024
- [c8]Elsa Rizk, Kun Yuan, Ali H. Sayed:
Asynchronous Diffusion Learning with Agent Subsampling and Local Updates. ICASSP 2024: 9246-9250 - [i13]Elsa Rizk, Kun Yuan, Ali H. Sayed:
Asynchronous Diffusion Learning with Agent Subsampling and Local Updates. CoRR abs/2402.05529 (2024) - 2023
- [j4]Elsa Rizk, Stefan Vlaski, Ali H. Sayed:
Privatized graph federated learning. EURASIP J. Adv. Signal Process. 2023(1): 87 (2023) - [j3]Elsa Rizk, Stefan Vlaski, Ali H. Sayed:
Enforcing Privacy in Distributed Learning With Performance Guarantees. IEEE Trans. Signal Process. 71: 3385-3398 (2023) - [c7]Ying Cao, Elsa Rizk, Stefan Vlaski, Ali H. Sayed:
Multi-Agent Adversarial Training Using Diffusion Learning. ICASSP 2023: 1-5 - [c6]Elsa Rizk, Stefan Vlaski, Ali H. Sayed:
Local Graph-Homomorphic Processing for Privatized Distributed Systems. ICASSP 2023: 1-5 - [i12]Elsa Rizk, Stefan Vlaski, Ali H. Sayed:
Enforcing Privacy in Distributed Learning with Performance Guarantees. CoRR abs/2301.06412 (2023) - [i11]Ying Cao, Elsa Rizk, Stefan Vlaski, Ali H. Sayed:
Multi-Agent Adversarial Training Using Diffusion Learning. CoRR abs/2303.01936 (2023) - [i10]Ying Cao, Elsa Rizk, Stefan Vlaski, Ali H. Sayed:
Decentralized Adversarial Training over Graphs. CoRR abs/2303.13326 (2023) - 2022
- [j2]Elsa Rizk, Stefan Vlaski, Ali H. Sayed:
Federated Learning Under Importance Sampling. IEEE Trans. Signal Process. 70: 5381-5396 (2022) - [c5]Maha Issa, Roula Nassif, Elsa Rizk, Ali H. Sayed:
Decentralized Semi-supervised Learning over Multitask Graphs. IEEECONF 2022: 419-425 - [i9]Elsa Rizk, Stefan Vlaski, Ali H. Sayed:
Privatized Graph Federated Learning. CoRR abs/2203.07105 (2022) - [i8]Elsa Rizk, Stefan Vlaski, Ali H. Sayed:
Local Graph-homomorphic Processing for Privatized Distributed Systems. CoRR abs/2210.15414 (2022) - 2021
- [c4]Elsa Rizk, Stefan Vlaski, Ali H. Sayed:
Optimal Importance Sampling for Federated Learning. ICASSP 2021: 3095-3099 - [c3]Elsa Rizk, Ali H. Sayed:
A Graph Federated Architecture with Privacy Preserving Learning. SPAWC 2021: 131-135 - [i7]Elsa Rizk, Ali H. Sayed:
A Graph Federated Architecture with Privacy Preserving Learning. CoRR abs/2104.13215 (2021) - 2020
- [j1]Stefan Vlaski, Elsa Rizk, Ali H. Sayed:
Tracking Performance of Online Stochastic Learners. IEEE Signal Process. Lett. 27: 1385-1389 (2020) - [c2]Stefan Vlaski, Elsa Rizk, Ali H. Sayed:
Second-Order Guarantees in Federated Learning. ACSSC 2020: 915-922 - [c1]Elsa Rizk, Stefan Vlaski, Ali H. Sayed:
Dynamic Federated Learning. SPAWC 2020: 1-5 - [i6]Elsa Rizk, Stefan Vlaski, Ali H. Sayed:
Dynamic Federated Learning. CoRR abs/2002.08782 (2020) - [i5]Stefan Vlaski, Elsa Rizk, Ali H. Sayed:
Tracking Performance of Online Stochastic Learners. CoRR abs/2004.01942 (2020) - [i4]Elsa Rizk, Stefan Vlaski, Ali H. Sayed:
Optimal Importance Sampling for Federated Learning. CoRR abs/2010.13600 (2020) - [i3]Stefan Vlaski, Elsa Rizk, Ali H. Sayed:
Second-Order Guarantees in Federated Learning. CoRR abs/2012.01474 (2020) - [i2]Elsa Rizk, Stefan Vlaski, Ali H. Sayed:
Federated Learning under Importance Sampling. CoRR abs/2012.07383 (2020)
2010 – 2019
- 2019
- [i1]Elsa Rizk, Roula Nassif, Ali H. Sayed:
Network Classifiers With Output Smoothing. CoRR abs/1911.04870 (2019)
Coauthor Index
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