7 citations · 12 across the 7 of their papers we have counts for
8 papers
Variance-Based Defense Against Blended Backdoor Attacks
Sujeevan Aseervatham, Achraf Kerzazi, Younès Bennani
Backdoor attacks represent a subtle yet effective class of cyberattacks targeting AI models, primarily due to their stealthy nature. The model behaves normally on clean data but ex…
Collaborative Multi-source Domain Adaptation Through Optimal Transport
Omar Ghannou, Younès Bennani
Multi-source Domain Adaptation (MDA) seeks to adapt models trained on data from multiple labeled source domains to perform effectively on an unlabeled target domain data, assuming…
Theoretical Guarantees for Domain Adaptation with Hierarchical Optimal Transport
Mourad El Hamri, Younès Bennani, Issam Falih
Domain adaptation arises as an important problem in statistical learning theory when the data-generating processes differ between training and test samples, respectively called sou…
A quantum learning approach based on Hidden Markov Models for failure scenarios generation
Ahmed Zaiou, Younès Bennani, Basarab Matei +1
Finding the failure scenarios of a system is a very complex problem in the field of Probabilistic Safety Assessment (PSA). In order to solve this problem we will use the Hidden Qua…
Convex Non-negative Matrix Factorization Through Quantum Annealing
Ahmed Zaiou, Basarab Matei, Younès Bennani +1
In this paper we provide the quantum version of the Convex Non-negative Matrix Factorization algorithm (Convex-NMF) by using the D-wave quantum annealer. More precisely, we use D-w…
Inductive Semi-supervised Learning Through Optimal Transport
Mourad El Hamri, Younès Bennani, Issam Falih
In this paper, we tackle the inductive semi-supervised learning problem that aims to obtain label predictions for out-of-sample data. The proposed approach, called Optimal Transpor…
Hierarchical Optimal Transport for Unsupervised Domain Adaptation
Mourad El Hamri, Younès Bennani, Issam Falih +1
In this paper, we propose a novel approach for unsupervised domain adaptation, that relates notions of optimal transport, learning probability measures and unsupervised learning. T…
Label Propagation Through Optimal Transport
Mourad El Hamri, Younès Bennani, Issam Falih
In this paper, we tackle the transductive semi-supervised learning problem that aims to obtain label predictions for the given unlabeled data points according to Vapnik's principle…