What is it about?
In this note, a novel way is proposed to find a low rank solution to a linear semi-definite feasibility problem through solving a concave minimization problem.
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Why is it important?
The proposed method to find a low rank solution to a linear semi-definite feasibility problem is something novel in the literature, which is by linking the problem to a concave minimization problem.
Perspectives
This note is a generalization of finding a solution with the most number of zeros to a linear system in the space of vectors to a lowest rank matrix to a linear system in the space of symmetric matrices.
Dr Chee Khian Sim
University of Portsmouth
Read the Original
This page is a summary of: On finding a generalized lowest rank solution to a linear semi-definite feasibility problem, Operations Research Letters, May 2015, Elsevier,
DOI: 10.1016/j.orl.2015.04.003.
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