Low-Rank Matrix Estimation From Rank-One Projections by Unlifted Convex Optimization

6 Apr 2020Sohail BahmaniKiryung Lee

We study an estimator with a convex formulation for recovery of low-rank matrices from rank-one projections. Using initial estimates of the factors of the target $d_1\times d_2$ matrix of rank-$r$, the estimator operates as a standard quadratic program in a space of dimension $r(d_1+d_2)$... (read more)

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