139 citations · 163 across the 3 of their papers we have counts for
5 papers
Tensor estimation with structured priors
Clément Luneau, Nicolas Macris
We consider rank-one symmetric tensor estimation when the tensor is corrupted by Gaussian noise and the spike forming the tensor is a structured signal coming from a generalized li…
Information theoretic limits of learning a sparse rule
Clément Luneau, Jean Barbier, Nicolas Macris
We consider generalized linear models in regimes where the number of nonzero components of the signal and accessible data points are sublinear with respect to the size of the signa…
High-dimensional rank-one nonsymmetric matrix decomposition: the spherical case
Clément Luneau, Nicolas Macris, Jean Barbier
We consider the problem of estimating a rank-one nonsymmetric matrix under additive white Gaussian noise. The matrix to estimate can be written as the outer product of two vectors…
Mutual information for low-rank even-order symmetric tensor estimation
Clément Luneau, Jean Barbier, Nicolas Macris
We consider a statistical model for finite-rank symmetric tensor factorization and prove a single-letter variational expression for its asymptotic mutual information when the tenso…
Entropy and mutual information in models of deep neural networks
Marylou Gabrié, Andre Manoel, Clément Luneau +4
We examine a class of deep learning models with a tractable method to compute information-theoretic quantities. Our contributions are three-fold: (i) We show how entropies and mutu…