Sarhad Arisdakessian

Orcid: 0009-0006-3210-4076

According to our database1, Sarhad Arisdakessian authored at least 14 papers between 2020 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Towards Vox Populi in Federated Learning: A Fair and Inclusive Client Selection Framework.
IEEE Trans. Artif. Intell., April, 2026

FL-PBM: Pre-Training Backdoor Mitigation for Federated Learning.
CoRR, March, 2026

Mitigating Backdoor Attacks in Federated Learning Using PPA and MiniMax Game Theory.
CoRR, March, 2026

Designing Federated Learning Marketplaces: Incentives, Network Dynamics, and Decentralized Learning.
IEEE Trans. Netw. Sci. Eng., 2026

A Two-Level Dirichlet Framework for Heterogeneous Federated Network.
IEEE Trans. Netw. Sci. Eng., 2026

2025
Enhancing Mutual Trustworthiness in Federated Learning for Data-Rich Smart Cities.
IEEE Internet Things J., 2025

2024
The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions.
IEEE Commun. Surv. Tutorials, 2024

2023
A Survey on IoT Intrusion Detection: Federated Learning, Game Theory, Social Psychology, and Explainable AI as Future Directions.
IEEE Internet Things J., March, 2023

Coalitional Federated Learning: Improving Communication and Training on Non-IID Data With Selfish Clients.
IEEE Trans. Serv. Comput., 2023

FedMint: Intelligent Bilateral Client Selection in Federated Learning With Newcomer IoT Devices.
IEEE Internet Things J., 2023

Towards Instant Clustering Approach for Federated Learning Client Selection.
Proceedings of the International Conference on Computing, Networking and Communications, 2023

2022
Machine Learning Based Container Placement in On-Demand Clustered Fogs.
Proceedings of the 2022 International Wireless Communications and Mobile Computing, 2022

Towards Bilateral Client Selection in Federated Learning Using Matching Game Theory.
Proceedings of the IEEE Global Communications Conference, 2022

2020
FoGMatch: An Intelligent Multi-Criteria IoT-Fog Scheduling Approach Using Game Theory.
IEEE/ACM Trans. Netw., 2020


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