4 citations · 5 across the 2 of their papers we have counts for
2 papers
cond-mat.dis-nn2024★ 1 cited
On the phase diagram of extensive-rank symmetric matrix denoising beyond rotational invariance
Jean Barbier, Francesco Camilli, Justin Ko +1
Matrix denoising is central to signal processing and machine learning. Its statistical analysis when the matrix to infer has a factorised structure with a rank growing proportional…
cs.IT2024★ 4 cited
A multiscale cavity method for sublinear-rank symmetric matrix factorization
Jean Barbier, Justin Ko, Anas A. Rahman
We consider a statistical model for symmetric matrix factorization with additive Gaussian noise in the high-dimensional regime, where the rank of the signal matrix to infer sca…