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Mario Chahoud
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2020 – today
- 2024
- [i4]Mario Chahoud, Azzam Mourad, Hadi Otrok, Jamal Bentahar, Mohsen Guizani:
Trust Driven On-Demand Scheme for Client Deployment in Federated Learning. CoRR abs/2405.00395 (2024) - [i3]Mario Chahoud, Hani Sami, Azzam Mourad, Hadi Otrok, Jamal Bentahar, Mohsen Guizani:
On-Demand Model and Client Deployment in Federated Learning with Deep Reinforcement Learning. CoRR abs/2405.07175 (2024) - 2023
- [j2]Mario Chahoud, Hani Sami
, Azzam Mourad
On-Demand-FL: A Dynamic and Efficient Multicriteria Federated Learning Client Deployment Scheme. IEEE Internet Things J. 10(18): 15822-15834 (2023) - [j1]Mario Chahoud
On the feasibility of Federated Learning towards on-demand client deployment at the edge. Inf. Process. Manag. 60(1): 103150 (2023) - [c2]Mario Chahoud, Azzam Mourad, Hadi Otrok, Mohsen Guizani:
Towards Trust Driven On-Demand Client Deployment in Federated Learning. INFOCOM Workshops 2023: 1-6 - [c1]Mario Chahoud, Hani Sami, Azzam Mourad, Hadi Otrok, Jamal Bentahar
Towards On-Demand Deployment of Multiple Clients and Heterogeneous Models in Federated Learning. IWCMC 2023: 1556-1561 - [i2]Hani Sami, Ahmad Hammoud, Mohamad Arafeh, Mohamad Wazzeh, Sarhad Arisdakessian, Mario Chahoud, Osama Wehbi
The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions. CoRR abs/2304.09240 (2023) - 2022
- [i1]Mario Chahoud, Hani Sami, Azzam Mourad, Safa Otoum, Hadi Otrok, Jamal Bentahar
ON-DEMAND-FL: A Dynamic and Efficient Multi-Criteria Federated Learning Client Deployment Scheme. CoRR abs/2211.02906 (2022)
Coauthor Index
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