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cs.IT2020
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…
cs.IT2020
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…
cs.IT2019
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…