Recovery of Low Rank Symmetric Matrices via Schatten Norm Minimization
L Cui, L Liu, DR Chen, JF Xie - Asia-Pacific Journal of Operational …, 2016 - World Scientific
L Cui, L Liu, DR Chen, JF Xie
Asia-Pacific Journal of Operational Research, 2016•World ScientificIn this paper, we give an application of the perturbation inequality to the low rank matrix
recovery problem and provide a condition on the linear map of underdetermined linear
system that every minimal rank symmetric matrix X∈ ℝ m× n can be exactly recovered from
the linear measurement b= 𝒜 (X)∈ ℝ q via some Schatten p 0 norm minimization. Moreover
it is shown that the explicit bound on exponent p 0 in the Schatten p 0 norm minimization can
be exactly extracted.
recovery problem and provide a condition on the linear map of underdetermined linear
system that every minimal rank symmetric matrix X∈ ℝ m× n can be exactly recovered from
the linear measurement b= 𝒜 (X)∈ ℝ q via some Schatten p 0 norm minimization. Moreover
it is shown that the explicit bound on exponent p 0 in the Schatten p 0 norm minimization can
be exactly extracted.
In this paper, we give an application of the perturbation inequality to the low rank matrix recovery problem and provide a condition on the linear map of underdetermined linear system that every minimal rank symmetric matrix can be exactly recovered from the linear measurement via some Schatten norm minimization. Moreover it is shown that the explicit bound on exponent in the Schatten norm minimization can be exactly extracted.
World ScientificShowing the best result for this search. See all results