212 citations · 370 across the 6 of their papers we have counts for
10 papers
Asymptotic Bayes risk for Gaussian mixture in a semi-supervised setting
Marc Lelarge, Leo Miolane
Semi-supervised learning (SSL) uses unlabeled data for training and has been shown to greatly improve performance when compared to a supervised approach on the labeled data availab…
Statistical thresholds for Tensor PCA
Aukosh Jagannath, Patrick Lopatto, Leo Miolane
We study the statistical limits of testing and estimation for a rank one deformation of a Gaussian random tensor. We compute the sharp thresholds for hypothesis testing and estimat…
The distribution of the Lasso: Uniform control over sparse balls and adaptive parameter tuning
Léo Miolane, Andrea Montanari
The Lasso is a popular regression method for high-dimensional problems in which the number of parameters , is larger than the number of samples: . A useful…
Phase transitions in spiked matrix estimation: information-theoretic analysis
Léo Miolane
We study here the so-called spiked Wigner and Wishart models, where one observes a low-rank matrix perturbed by some Gaussian noise. These models encompass many classical statistic…
The Layered Structure of Tensor Estimation and its Mutual Information
Jean Barbier, Nicolas Macris, Léo Miolane
We consider rank-one non-symmetric tensor estimation and derive simple formulas for the mutual information. We start by the order 2 problem, namely matrix factorization. We treat i…
Optimal Errors and Phase Transitions in High-Dimensional Generalized Linear Models
Jean Barbier, Florent Krzakala, Nicolas Macris +2
Generalized linear models (GLMs) arise in high-dimensional machine learning, statistics, communications and signal processing. In this paper we analyze GLMs when the data matrix is…