3 papers
cs.LG2025
Wasserstein Distributionally Robust Shallow Convex Neural Networks
Julien Pallage, Antoine Lesage-Landry
In this work, we propose Wasserstein distributionally robust shallow convex neural networks (WaDiRo-SCNNs) to provide reliable nonlinear predictions when subject to adverse and cor…
cs.LG2025
Sliced-Wasserstein Distance-based Data Selection
Julien Pallage, Antoine Lesage-Landry
We propose a new unsupervised anomaly detection method based on the sliced-Wasserstein distance for training data selection in machine learning approaches. Our filtering technique…
cs.LG2024
Sliced-Wasserstein-based Anomaly Detection and Open Dataset for Localized Critical Peak Rebates
Julien Pallage, Bertrand Scherrer, Salma Naccache +2
In this work, we present a new unsupervised anomaly (outlier) detection (AD) method using the sliced-Wasserstein metric. This filtering technique is conceptually interesting for ML…