Low-rank matrix estimation with inhomogeneous noise
We study low-rank matrix estimation for a generic inhomogeneous output channel through which the matrix is observed. This generalizes the commonly considered spiked matrix model with homogeneous noise to include for instance the dense degree-corrected stochastic block model. We adapt techniques used to study multi-species spin glasses to derive and rigorously prove an expression for the free energy of the problem in the large size limit, providing a framework to study the signal detection thresholds. We discuss an application of this framework to the degree corrected stochastic block models.
2-s2.0-105002830677
Unité de Mathématiques Pures et Appliquées de l'ENS de Lyon
Unité de Mathématiques Pures et Appliquées de l'ENS de Lyon
École Polytechnique Fédérale de Lausanne
École Polytechnique Fédérale de Lausanne
2025-06-01
14
2
iaaf010
REVIEWED
EPFL
| Funder | Funding(s) | Grant Number | Grant URL |
European Research Council | |||
European Union Horizon 2020 research and innovation pro-gramme | |||
European Union Horizon 2020 research and innovation programme | 884584 | ||
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