15 citations · 33 across the 12 of their papers we have counts for
12 papers
Channel Estimation in RIS-Enabled mmWave Wireless Systems: A Variational Inference Approach
Firas Fredj, Amal Feriani, Amine Mezghani +1
Channel estimation in reconfigurable intelligent surfaces (RIS)-aided systems is crucial for optimal configuration of the RIS and various downstream tasks such as user localization…
CeBed: A Benchmark for Deep Data-Driven OFDM Channel Estimation
Amal Feriani, Di Wu, Steve Liu +1
Deep learning has been extensively used in wireless communication problems, including channel estimation. Although several data-driven approaches exist, a fair and realistic compar…
Mixed-Variable PSO with Fairness on Multi-Objective Field Data Replication in Wireless Networks
Dun Yuan, Yujin Nam, Amal Feriani +5
Digital twins have shown a great potential in supporting the development of wireless networks. They are virtual representations of 5G/6G systems enabling the design of machine lear…
Domain Generalization in Machine Learning Models for Wireless Communications: Concepts, State-of-the-Art, and Open Issues
Mohamed Akrout, Amal Feriani, Faouzi Bellili +2
Data-driven machine learning (ML) is promoted as one potential technology to be used in next-generations wireless systems. This led to a large body of research work that applies ML…
Continual Learning-Based MIMO Channel Estimation: A Benchmarking Study
Mohamed Akrout, Amal Feriani, Faouzi Bellili +2
With the proliferation of deep learning techniques for wireless communication, several works have adopted learning-based approaches to solve the channel estimation problem. While t…
A 35-Year Longitudinal Analysis of Dermatology Patient Behavior across Economic & Cultural Manifestations in Tunisia, and the Impact of Digital Tools
Mohamed Akrout, Hayet Amdouni, Amal Feriani +2
The evolution of behavior of dermatology patients has seen significantly accelerated change over the past decade, driven by surging availability and adoption of digital tools and p…
Dynamic Noises of Multi-Agent Environments Can Improve Generalization: Agent-based Models meets Reinforcement Learning
Mohamed Akrout, Amal Feriani, Bob McLeod
We study the benefits of reinforcement learning (RL) environments based on agent-based models (ABM). While ABMs are known to offer microfoundational simulations at the cost of comp…
On the Robustness of Deep Reinforcement Learning in IRS-Aided Wireless Communications Systems
Amal Feriani, Amine Mezghani, Ekram Hossain
We consider an Intelligent Reflecting Surface (IRS)-aided multiple-input single-output (MISO) system for downlink transmission. We compare the performance of Deep Reinforcement Lea…
Decentralized Multi-Agent Reinforcement Learning for Task Offloading Under Uncertainty
Yuanchao Xu, Amal Feriani, Ekram Hossain
Multi-Agent Reinforcement Learning (MARL) is a challenging subarea of Reinforcement Learning due to the non-stationarity of the environments and the large dimensionality of the com…
Single and Multi-Agent Deep Reinforcement Learning for AI-Enabled Wireless Networks: A Tutorial
Amal Feriani, Ekram Hossain
Deep Reinforcement Learning (DRL) has recently witnessed significant advances that have led to multiple successes in solving sequential decision-making problems in various domains,…
Hacking Google reCAPTCHA v3 using Reinforcement Learning
Ismail Akrout, Amal Feriani, Mohamed Akrout
We present a Reinforcement Learning (RL) methodology to bypass Google reCAPTCHA v3. We formulate the problem as a grid world where the agent learns how to move the mouse and click…
DVOLVER: Efficient Pareto-Optimal Neural Network Architecture Search
Guillaume Michel, Mohammed Amine Alaoui, Alice Lebois +2
Automatic search of neural network architectures is a standing research topic. In addition to the fact that it presents a faster alternative to hand-designed architectures, it can…