activity
20212024
most citedLabel Propagation Through Optimal Transport

7 citations · 13 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV2024

Skeleton-Based Action Recognition with Spatial-Structural Graph Convolution

Jingyao Wang, Emmanuel Bergeret, Issam Falih

Human Activity Recognition (HAR) is a field of study that focuses on identifying and classifying human activities. Skeleton-based Human Activity Recognition has received much atten…

cs.CV2022★ 1 cited

A comparative study of emotion recognition methods using facial expressions

Rim EL Cheikh, Hélène Tran, Issam Falih +1

Understanding the facial expressions of our interlocutor is important to enrich the communication and to give it a depth that goes beyond the explicitly expressed. In fact, studyin…

stat.ML2022★ 1 cited

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…

stat.ML2021★ 4 cited

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…

cs.CV2021

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…

cs.LG2021★ 7 cited

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…