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stat.ML2026
On Finite-sample Concentration of Median of Incomplete U-Statistics
Nong Minh Hieu, Antoine Ledent
Median-of-means (MoM) is a powerful technique that theoretically enables near sub-Gaussian finite-sample rate for parameter estimation when the underlying data distribution is heav…
stat.ML2026
A Refined Generalization Analysis for Extreme Multi-class Supervised Contrastive Representation Learning
Nong Minh Hieu, Antoine Ledent
Contrastive Representation Learning (CRL) has achieved strong empirical success in multiple machine learning disciplines, yet its theoretical sample complexity remains poorly under…
cs.LG2026
Scalable Multi-Task Low-Rank Model Adaptation
Zichen Tian, Antoine Ledent, Qianru Sun
Scaling multi-task low-rank adaptation (LoRA) to a large number of tasks induces catastrophic performance degradation, such as an accuracy drop from 88.2% to 2.0% on DOTA when scal…