5 papers
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…
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…
Generalization Bounds for Semi-supervised Matrix Completion with Distributional Side Information
Antoine Ledent, Mun Chong Soo, Nong Minh Hieu
We study a matrix completion problem where both the ground truth matrix and the unknown sampling distribution over observed entries are low-rank matrices, and \textit{share…
Generalization Analysis for Supervised Contrastive Representation Learning under Non-IID Settings
Nong Minh Hieu, Antoine Ledent
Contrastive Representation Learning (CRL) has achieved impressive success in various domains in recent years. Nevertheless, the theoretical understanding of the generalization beha…
Generalization Analysis for Deep Contrastive Representation Learning
Nong Minh Hieu, Antoine Ledent, Yunwen Lei +1
In this paper, we present generalization bounds for the unsupervised risk in the Deep Contrastive Representation Learning framework, which employs deep neural networks as represent…