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Low-rank Solutions of Linear Matrix Equations via Procrustes Flow

ICML 2016 · Optimization › Implicit bias and generalization · approach: Low-rank and single-index recovery · 139 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add spectral (projected gradient) initialization phase before gradient descentProcrustes Flow for low-rank matrix recovery · theoretical analysis (RIP, Gaussian ensemble)sample complexity / convergence guaranteeNo clear effect
Use Omega(nr) Gaussian measurements instead of Omega(nr^3 kappa^2 log n) (Zheng & Lafferty)gradient descent on Procrustes Flow objective · Gaussian ensemble theoryrequired number of measurementsHelped

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