3 papers
stat.ML2025
High-Dimensional Partial Least Squares: Spectral Analysis and Fundamental Limitations
Victor Léger, Florent Chatelain
Partial Least Squares (PLS) is a widely used method for data integration, designed to extract latent components shared across paired high-dimensional datasets. Despite decades of p…
stat.ML2024
Asymptotic Bayes risk of semi-supervised learning with uncertain labeling
Victor Leger, Romain Couillet
This article considers a semi-supervised classification setting on a Gaussian mixture model, where the data is not labeled strictly as usual, but instead with uncertain labels. Our…
stat.ML2024
A Large Dimensional Analysis of Multi-task Semi-Supervised Learning
Victor Leger, Romain Couillet
This article conducts a large dimensional study of a simple yet quite versatile classification model, encompassing at once multi-task and semi-supervised learning, and taking into…