Mario Chahoud

According to our database, Mario Chahoud authored at least 8 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

On-Demand Model and Client Deployment in Federated Learning with Deep Reinforcement Learning.

Mario Chahoud, Hani Sami, Azzam Mourad, Hadi Otrok, Jamal Bentahar, Mohsen Guizani

CoRR, 2024

Trust Driven On-Demand Scheme for Client Deployment in Federated Learning.

Mario Chahoud, Azzam Mourad, Hadi Otrok, Jamal Bentahar, Mohsen Guizani

CoRR, 2024

2023

On-Demand-FL: A Dynamic and Efficient Multicriteria Federated Learning Client Deployment Scheme.

Mario Chahoud, Hani Sami, Azzam Mourad, Safa Otoum, Hadi Otrok, Jamal Bentahar, Mohsen Guizani

IEEE Internet Things J., September, 2023

On the feasibility of Federated Learning towards on-demand client deployment at the edge.

Mario Chahoud, Safa Otoum, Azzam Mourad

Inf. Process. Manag., 2023

The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions.

Hani Sami, Ahmad Hammoud, Mohamad Arafeh, Mohamad Wazzeh, Sarhad Arisdakessian, Mario Chahoud, Osama Wehbi, Mohamad Ajaj, Azzam Mourad, Hadi Otrok, Omar Abdel Wahab, Rabeb Mizouni, Jamal Bentahar, Chamseddine Talhi, Zbigniew Dziong, Ernesto Damiani, Mohsen Guizani

CoRR, 2023

Towards On-Demand Deployment of Multiple Clients and Heterogeneous Models in Federated Learning.

Mario Chahoud, Hani Sami, Azzam Mourad, Hadi Otrok, Jamal Bentahar, Mohsen Guizani

Proceedings of the International Wireless Communications and Mobile Computing, 2023

Towards Trust Driven On-Demand Client Deployment in Federated Learning.

Mario Chahoud, Azzam Mourad, Hadi Otrok, Mohsen Guizani

Proceedings of the IEEE INFOCOM 2023, 2023

2022

ON-DEMAND-FL: A Dynamic and Efficient Multi-Criteria Federated Learning Client Deployment Scheme.

Mario Chahoud, Hani Sami, Azzam Mourad, Safa Otoum, Hadi Otrok, Jamal Bentahar, Mohsen Guizani

CoRR, 2022