Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach
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چکیده
We consider the non-square matrix sensing problem, under restricted isometry property (RIP) assumptions. We focus on the non-convex formulation, where any rank-r matrix X ∈ R is represented as UV , where U ∈ R and V ∈ R. In this paper, we complement recent findings on the nonconvex geometry of the analogous PSD setting [5], and show that matrix factorization does not introduce any spurious local minima, under RIP.
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تاریخ انتشار 2017