3 citations · 6 across the 5 of their papers we have counts for
5 papers
Rectangular Rotational Invariant Estimator for High-Rank Matrix Estimation
Farzad Pourkamali, Nicolas Macris
We consider estimating a matrix from noisy observations coming from an arbitrary additive bi-rotational invariant perturbation. We propose an estimator which is optimal among the c…
Bayesian Extensive-Rank Matrix Factorization with Rotational Invariant Priors
Farzad Pourkamali, Nicolas Macris
We consider a statistical model for matrix factorization in a regime where the rank of the two hidden matrix factors grows linearly with their dimension and their product is corrup…
Matrix Inference in Growing Rank Regimes
Farzad Pourkamali, Jean Barbier, Nicolas Macris
The inference of a large symmetric signal-matrix corrupted by additive Gaussian noise, is considered for two regimes of growth of the rank $…
Rectangular Rotational Invariant Estimator for General Additive Noise Matrices
Farzad Pourkamali, Nicolas Macris
We propose a rectangular rotational invariant estimator to recover a real matrix from noisy matrix observations coming from an arbitrary additive rotational invariant perturbation,…
Mismatched Estimation of rank-one symmetric matrices under Gaussian noise
Farzad Pourkamali, Nicolas Macris
We consider the estimation of an n-dimensional vector s from the noisy element-wise measurements of , a generic problem that arises in statistics and machin…