most citedA Green Multi-Attribute Client Selection for Over-The-Air Federated Learning: A Grey-Wolf-Optimizer Approach

1 citations · 1 across the 1 of their papers we have counts for

collaborators
Showing cs.NIShow all

2 papers · 1 filter

cs.NI2026

DisC: Incentive Design for Green, Robust, and Fair Client Self-Participation in OTA Federated Learning

Driss Choukri, Essaid Sabir, Abdelkrim Haqiq

Over-the-Air Federated Learning (OTA-FL) improves communication efficiency by exploiting waveform superposition over wireless Multiple-Access Channels (MAC). However, client hetero…

cs.NI2026

FedMaJ: Ordinal Meta-Aggregation for Federated Learning Using Majority-Judgment Voting

Driss Choukri, Essaid Sabir, Halima Elbiaze +1

Federated learning traditionally relies on a fixed aggregation rule despite shifting client state and wireless dynamics. We present FedMaJ, a framework that dynamically selects agg…