55 citations · 72 across the 5 of their papers we have counts for
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Lecture notes on non-convex algorithms for low-rank matrix recovery
Irène Waldspurger
Low-rank matrix recovery problems are inverse problems which naturally arise in various fields like signal processing, imaging and machine learning. They are non-convex and NP-hard…
Rank optimality for the Burer-Monteiro factorization
Irène Waldspurger, Alden Waters
When solving large scale semidefinite programs that admit a low-rank solution, an efficient heuristic is the Burer-Monteiro factorization: instead of optimizing over the full matri…
Phase retrieval for wavelet transforms
Irène Waldspurger
We describe a new algorithm to solve a particular phase retrieval problem, that has wide applications in audio processing: the reconstruction of a function from its scalogram, that…
Phase retrieval for imaging problems
Fajwel Fogel, Irène Waldspurger, Alexandre d'Aspremont
We study convex relaxation algorithms for phase retrieval on imaging problems. We show that structural assumptions on the signal and the observations, such as sparsity, smoothness…
Phase Recovery, MaxCut and Complex Semidefinite Programming
Irène Waldspurger, Alexandre d'Aspremont, Stéphane Mallat
Phase retrieval seeks to recover a signal x from the amplitude |Ax| of linear measurements. We cast the phase retrieval problem as a non-convex quadratic program over a complex pha…