On finding a generalized lowest rank solution to a linear semi-definite feasibility problem

DOI10.1016/j.orl.2015.04.003zbMath1408.90230OpenAlexW2035099674WikidataQ58028353 ScholiaQ58028353MaRDI QIDQ1785372

Chee-Khian Sim

Publication date: 28 September 2018

Published in: Operations Research Letters (Search for Journal in Brave)

Full work available at URL: https://researchportal.port.ac.uk/portal/en/publications/on-finding-a-generalized-lowest-rank-solution-to-a-linear-semidefinite-feasibility-problem(af3ad478-7d2f-4026-a44b-978fd5bdf6ed).html

zbMATH Keywords

concave minimization problemaffine rank minimization problemvector cardinality minimization problem

Mathematics Subject Classification ID

Semidefinite programming (90C22) Vector spaces, linear dependence, rank, lineability (15A03)

Cites Work

• An approximation theory of matrix rank minimization and its application to quadratic equations
• A note on the complexity of \(L _{p }\) minimization
• Equivalence of minimal \(\ell _{0}\)- and \(\ell _{p }\)-norm solutions of linear equalities, inequalities and linear programs for sufficiently small \(p\)
• Concave programming for minimizing the zero-norm over polyhedral sets
• Nonsmooth analysis of eigenvalues
• Decoding by Linear Programming
• Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
• Methods for Global Concave Minimization: A Bibliographic Survey
• Deterministic algorithms for constrained concave minimization: A unified critical survey
• Group Invariance and Convex Matrix Analysis
• Reweighted $\ell_1$-Minimization for Sparse Solutions to Underdetermined Linear Systems
• Conditional Gradient Algorithmsfor Rank-One Matrix Approximations with a Sparsity Constraint
• Convex Analysis

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