3 papers
stat.ML2026
Improved Analysis of the Accelerated Noisy Power Method with Applications to Decentralized PCA
Pierre Aguié, Mathieu Even, Laurent Massoulié
We analyze the Accelerated Noisy Power Method, an algorithm for Principal Component Analysis in the setting where only inexact matrix-vector products are available, which can arise…
cs.LG2025
Meta-learning of shared linear representations beyond well-specified linear regression
Mathieu Even, Laurent Massoulié
Motivated by multi-task and meta-learning approaches, we consider the problem of learning structure shared by tasks or users, such as shared low-rank representations or clustered s…
stat.ML2025
Concentration of Non-Isotropic Random Tensors with Applications to Learning and Empirical Risk Minimization
Mathieu Even, Laurent Massoulié
Dimension is an inherent bottleneck to some modern learning tasks, where optimization methods suffer from the size of the data. In this paper, we study non-isotropic distributions…