3 papers
cs.LG2026
Implicit Regularization for Multi-label Feature Selection
Dou El Kefel Mansouri, Khalid Benabdeslem, Seif-Eddine Benkabou
In this paper, we address the problem of feature selection in the context of multi-label learning, by using a new estimator based on implicit regularization and label embedding. Un…
cs.CV2025
Embedding-Driven Data Distillation for 360-Degree IQA With Residual-Aware Refinement
Abderrezzaq Sendjasni, Seif-Eddine Benkabou, Mohamed-Chaker Larabi
This article identifies and addresses a fundamental bottleneck in data-driven 360-degree image quality assessment (IQA): the lack of intelligent, sample-level data selection. Hence…
stat.ML2025
Fréchet regression with implicit denoising and multicollinearity reduction
Dou El Kefel Mansouri, Seif-Eddine Benkabou, Khalid Benabdeslem
Fréchet regression extends linear regression to model complex responses in metric spaces, making it particularly relevant for multi-label regression, where eachinstance can have m…