4 citations · 6 across the 8 of their papers we have counts for
10 papers
Real-time Threat Detection Strategies for Resource-constrained Devices
Mounia Hamidouche, Biniam Fisseha Demissie, Bilel Cherif
As more devices connect to the internet, it becomes crucial to address their limitations and basic security needs. While much research focuses on utilizing ML and DL to tackle secu…
Enhancing IoT Security via Automatic Network Traffic Analysis: The Transition from Machine Learning to Deep Learning
Mounia Hamidouche, Eugeny Popko, Bassem Ouni
This work provides a comparative analysis illustrating how Deep Learning (DL) surpasses Machine Learning (ML) in addressing tasks within Internet of Things (IoT), such as attack cl…
White-box Membership Attack Against Machine Learning Based Retinopathy Classification
Mounia Hamidouche, Reda Bellafqira, Gwenolé Quellec +1
The advances in machine learning (ML) have greatly improved AI-based diagnosis aid systems in medical imaging. However, being based on collecting medical data specific to individua…
Graphs as Tools to Improve Deep Learning Methods
Carlos Lassance, Myriam Bontonou, Mounia Hamidouche +3
In recent years, deep neural networks (DNNs) have known an important rise in popularity. However, although they are state-of-the-art in many machine learning challenges, they still…
Improving Classification Accuracy with Graph Filtering
Mounia Hamidouche, Carlos Lassance, Yuqing Hu +3
In machine learning, classifiers are typically susceptible to noise in the training data. In this work, we aim at reducing intra-class noise with the help of graph filtering to imp…
Ranking Deep Learning Generalization using Label Variation in Latent Geometry Graphs
Carlos Lassance, Louis Béthune, Myriam Bontonou +2
Measuring the generalization performance of a Deep Neural Network (DNN) without relying on a validation set is a difficult task. In this work, we propose exploiting Latent Geometry…
Spectral bounds of the regularized normalized Laplacian for random geometric graphs
Mounia Hamidouche, Laura Cottatellucci, Konstantin Avrachenkov
In this work, we study the spectrum of the regularized normalized Laplacian for random geometric graphs (RGGs) in both the connectivity and thermodynamic regimes. We prove that the…
Spectral Analysis of the Adjacency Matrix of Random Geometric Graphs
Mounia Hamidouche, Laura Cottatellucci, Konstantin Avrachenkov
In this article, we analyze the limiting eigenvalue distribution (LED) of random geometric graphs (RGGs). The RGG is constructed by uniformly distributing nodes on the -dime…
Eigenvalues and Spectral Dimension of Random Geometric Graphs in Thermodynamic Regime
Konstantin Avrachenkov, Laura Cottatellucci, Mounia Hamidouche
Network geometries are typically characterized by having a finite spectral dimension (SD), that characterizes the return time distribution of a random walk on a graph. The…
Downlink Performance of Dense Antenna Deployment: To Distribute or Concentrate?
Mounia Hamidouche, Ejder Baştuğ, Jihong Park +2
Massive multiple-input multiple-output (massive MIMO) and small cell densification are complementary key 5G enablers. Given a fixed number of the entire base-station antennas per u…