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Global Optimality of Local Search for Low Rank Matrix Recovery

NeurIPS 2016 · Optimization › Implicit bias and generalization · approach: Low-rank and single-index recovery · 241 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add RIP-based incoherence condition (delta_2r<1/5) to factorized matrix sensing objectivefactorized non-convex matrix sensing f(U) · noiseless matrix sensingexistence of spurious local minimaHelped
Random initialization instead of SVD initialization for gradient descentfactorized gradient descent for matrix sensing · n=100 random PSD matrix sensingphase transition at m ~ 2nrNo clear effect
Counterexample: unconstrained rank-r and rank-1 objectives in Examples 1-2 without RIPfactorized objective without RIP · constructed low-rank examplesexistence of non-global local minimaHurt

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