4 citations · 4 across the 4 of their papers we have counts for
4 papers
FairEnergy: Contribution-Based Fairness meets Energy Efficiency in Federated Learning
Ouiame Marnissi, Hajar EL Hammouti, El Houcine Bergou
Federated learning (FL) enables collaborative model training across distributed devices while preserving data privacy. However, balancing energy efficiency and fair participation w…
Semantic-Aware Resource Allocation in Constrained Networks with Limited User Participation
Ouiame Marnissi, Hajar EL Hammouti, El Houcine Bergou
Semantic communication has gained attention as a key enabler for intelligent and context-aware communication. However, one of the key challenges of semantic communications is the n…
Joint Probability Selection and Power Allocation for Federated Learning
Ouiame Marnissi, Hajar EL Hammouti, El Houcine Bergou
In this paper, we study the performance of federated learning over wireless networks, where devices with a limited energy budget train a machine learning model. The federated learn…
Client Selection in Federated Learning based on Gradients Importance
Ouiame Marnissi, Hajar El Hammouti, El Houcine Bergou
Federated learning (FL) enables multiple devices to collaboratively learn a global model without sharing their personal data. In real-world applications, the different parties are…