275 citations · 822 across the 42 of their papers we have counts for
4 papers · 1 filter
Communication-Efficient Hierarchical Federated Learning for IoT Heterogeneous Systems with Imbalanced Data
Alaa Awad Abdellatif, Naram Mhaisen, Amr Mohamed +4
Federated learning (FL) is a distributed learning methodology that allows multiple nodes to cooperatively train a deep learning model, without the need to share their local data. I…
Analysis and Optimal Edge Assignment For Hierarchical Federated Learning on Non-IID Data
Naram Mhaisen, Alaa Awad, Amr Mohamed +2
Distributed learning algorithms aim to leverage distributed and diverse data stored at users' devices to learn a global phenomena by performing training amongst participating devic…
Multimodal deep learning approach for joint EEG-EMG data compression and classification
Ahmed Ben Said, Amr Mohamed, Tarek Elfouly +2
In this paper, we present a joint compression and classification approach of EEG and EMG signals using a deep learning approach. Specifically, we build our system based on the deep…
Distributed Cooperative Q-learning for Power Allocation in Cognitive Femtocell Networks
Hussein Saad, Amr Mohamed, Tamer ElBatt
In this paper, we propose a distributed reinforcement learning (RL) technique called distributed power control using Q-learning (DPC-Q) to manage the interference caused by the fem…