Maximal Generalized Rank in Graphical Matrix Spaces
Alexander Guterman, Roy Meshulam, Igor Spiridonov

TL;DR
This paper extends a combinatorial characterization of maximal bounded rank subspaces in graphical matrix spaces to generalized rank functions and to alternating matrix spaces for general graphs.
Contribution
It introduces two significant extensions of existing rank characterization results to broader classes of rank functions and matrix spaces.
Findings
Characterization valid for generalized rank functions including permanental rank
Extension to bounded rank subspaces of graphical alternating matrix spaces
Applicable to a wide class of bipartite and general graphs
Abstract
In this note we prove two extensions of a recent combinatorial characterization due to Li, Qiao, Wigderson, Wigderson and Zhang (arXiv:2206.04815) of the maximal dimension of bounded rank subspaces of the graphical matrix space associated with a bipartite graph. Our first result shows that the above characterization remains valid for a wide class of generalized rank functions, including e.g. the permanental rank. Our second result extends the characterization to bounded rank subspaces of the graphical alternating matrix space associated with a general graph.
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Taxonomy
TopicsDigital Image Processing Techniques · Sparse and Compressive Sensing Techniques · Fuzzy and Soft Set Theory
