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Diving for Sparse Partially-Reflexive Generalized Inverses

  • Victor K. Fuentes
  • Marcia Fampa
  • Jon LeeEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 991)

Abstract

Generalized inverses form a set of key tools in matrix algebra. For large-scale applications, sparsity is highly desirable, and so sparse generalized inverses have been studied. One such family is based on relaxing the well-known Moore-Penrose properties. One of those properties is non-linear, and so we develop a convex-programming relaxation and an associated “diving” heuristic to achieve a good trade-off between sparsity and satisfaction of the non-linear Moore-Penrose property.

Keywords

Generalized inverse Reflexive generalized inverse Moore-Penrose pseudoinverse Sparse optimization 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.University of MichiganAnn ArborUSA
  2. 2.Universidade Federal do Rio de JaneiroRio de JaneiroBrasil

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