Global Optimality in Low-Rank Matrix Optimization
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Publication:4622249
DOI10.1109/TSP.2018.2835403zbMath1414.90297arXiv1702.07945MaRDI QIDQ4622249
Qiuwei Li, Zhihui Zhu, Michael B. Wakin, Gongguo Tang
Publication date: 12 February 2019
Published in: IEEE Transactions on Signal Processing (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1702.07945
Related Items (16)
Role of sparsity and structure in the optimization landscape of non-convex matrix sensing ⋮ An Unbiased Approach to Low Rank Recovery ⋮ Unnamed Item ⋮ Column $\ell_{2,0}$-Norm Regularized Factorization Model of Low-Rank Matrix Recovery and Its Computation ⋮ GNMR: A Provable One-Line Algorithm for Low Rank Matrix Recovery ⋮ Finding stationary points on bounded-rank matrices: a geometric hurdle and a smooth remedy ⋮ Certifying the Absence of Spurious Local Minima at Infinity ⋮ An Equivalence between Critical Points for Rank Constraints Versus Low-Rank Factorizations ⋮ The global optimization geometry of shallow linear neural networks ⋮ Recovery of simultaneous low rank and two-way sparse coefficient matrices, a nonconvex approach ⋮ Nonconvex Robust Low-Rank Matrix Recovery ⋮ Error bound of critical points and KL property of exponent 1/2 for squared F-norm regularized factorization ⋮ Provable accelerated gradient method for nonconvex low rank optimization ⋮ Matrix completion via minimizing an approximate rank ⋮ Unnamed Item ⋮ Low rank matrix recovery with adversarial sparse noise*
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