2 citations · 2 across the 2 of their papers we have counts for
4 papers · 1 filter
Rank-one matrix estimation: analysis of algorithmic and information theoretic limits by the spatial coupling method
Jean Barbier, Mohamad Dia, Nicolas Macris +2
Factorizing low-rank matrices is a problem with many applications in machine learning and statistics, ranging from sparse PCA to community detection and sub-matrix localization. Fo…
A Compressed Sensing Approach for Distribution Matching
Mohamad Dia, Vahid Aref, Laurent Schmalen
In this work, we formulate the fixed-length distribution matching as a Bayesian inference problem. Our proposed solution is inspired from the compressed sensing paradigm and the sp…
Threshold Saturation of Spatially Coupled Sparse Superposition Codes for All Memoryless Channels
Jean Barbier, Mohamad Dia, Nicolas Macris
We recently proved threshold saturation for spatially coupled sparse superposition codes on the additive white Gaussian noise channel. Here we generalize our analysis to a much bro…
Proof of Threshold Saturation for Spatially Coupled Sparse Superposition Codes
Jean Barbier, Mohamad Dia, Nicolas Macris
Recently, a new class of codes, called sparse superposition or sparse regression codes, has been proposed for communication over the AWGN channel. It has been proven that they achi…