2.4k citations · 5.2k across the 108 of their papers we have counts for
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Sparsity-Aware Intelligent Massive Random Access Control in Open RAN: A Reinforcement Learning Based Approach
Xiao Tang, Sicong Liu, Xiaojiang Du +1
Massive random access of devices in the emerging Open Radio Access Network (O-RAN) brings great challenge to the access control and management. Exploiting the bursting nature of th…
RL-DistPrivacy: Privacy-Aware Distributed Deep Inference for low latency IoT systems
Emna Baccour, Aiman Erbad, Amr Mohamed +2
Although Deep Neural Networks (DNN) have become the backbone technology of several ubiquitous applications, their deployment in resource-constrained machines, e.g., Internet of Thi…
Reinforcement Learning for Intelligent Healthcare Systems: A Comprehensive Survey
Alaa Awad Abdellatif, Naram Mhaisen, Zina Chkirbene +3
The rapid increase in the percentage of chronic disease patients along with the recent pandemic pose immediate threats on healthcare expenditure and elevate causes of death. This c…
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…
Edge Intelligence for Empowering IoT-based Healthcare Systems
Vahideh Hayyolalam, Moayad Aloqaily, Oznur Ozkasap +1
The demand for real-time, affordable, and efficient smart healthcare services is increasing exponentially due to the technological revolution and burst of population. To meet the 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…
Budgeted Online Selection of Candidate IoT Clients to Participate in Federated Learning
Ihab Mohammed, Shadha Tabatabai, Ala Al-Fuqaha +4
Machine Learning (ML), and Deep Learning (DL) in particular, play a vital role in providing smart services to the industry. These techniques however suffer from privacy and securit…
Trust-Based Cloud Machine Learning Model Selection For Industrial IoT and Smart City Services
Basheer Qolomany, Ihab Mohammed, Ala Al-Fuqaha +2
With Machine Learning (ML) services now used in a number of mission-critical human-facing domains, ensuring the integrity and trustworthiness of ML models becomes all-important. In…