We consider a statistical model for matrix factorization in a regime whe...
The inference of a large symmetric signal-matrix 𝐒∈ℝ^N× N corrupted by a...
We propose a rectangular rotational invariant estimator to recover a rea...
In this work, we present a new approach to analyze the gradient flow for...
A recent line of work has shown remarkable behaviors of the generalizati...
Recent evidence has shown the existence of a so-called double-descent an...
We consider increasingly complex models of matrix denoising and dictiona...
We consider the estimation of an n-dimensional vector s from the noisy
e...
We consider a rank-one symmetric matrix corrupted by additive noise. The...
Non-linear partial differential Kolmogorov equations are successfully us...
We consider rank-one symmetric tensor estimation when the tensor is corr...
We consider generalized linear models in regimes where the number of
non...
We determine statistical and computational limits for estimation of a
ra...
We consider the problem of estimating a rank-one nonsymmetric matrix und...
We shortly review Bell-diagonal and Werner states of two quantum bits an...
We consider statistical models of estimation of a rank-one matrix (the s...
We consider a statistical model for finite-rank symmetric tensor
factori...
We rigorously derive a single-letter variational expression for the mutu...
In this contribution we give a pedagogic introduction to the newly intro...
Factorizing low-rank matrices is a problem with many applications in mac...
Heuristic tools from statistical physics have been used in the past to l...
A new adaptive path interpolation method has been recently developed as ...
We examine a class of deep learning models with a tractable method to co...
There has been definite progress recently in proving the variational
sin...
We consider generalized linear models (GLMs) where an unknown n-dimensio...