• DocumentCode
    3254696
  • Title

    A tightest convex envelope heuristic to row sparse and rank one matrices

  • Author

    Aghasi, Alireza ; Bahmani, Sohail ; Romberg, Justin

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
  • fYear
    2013
  • fDate
    3-5 Dec. 2013
  • Firstpage
    627
  • Lastpage
    627
  • Abstract
    The main result of this paper is providing a tight convex envelope to row sparse and rank one matrices which is of major interest in signal recovery applications. The resulting convexification turns out to be the ℓ1 norm of the matrix. This result highlights the fact that a joint convexification approach may not significantly improve the signal recovery process.
  • Keywords
    convex programming; heuristic programming; matrix algebra; convexification; matrix; rank one matrices; row sparse; signal recovery applications; signal recovery process; tight convex envelope heuristic; Approximation methods; Computers; Educational institutions; Joints; Linear matrix inequalities; Manganese; Sparse matrices;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Global Conference on Signal and Information Processing (GlobalSIP), 2013 IEEE
  • Conference_Location
    Austin, TX
  • Type

    conf

  • DOI
    10.1109/GlobalSIP.2013.6736964
  • Filename
    6736964
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3254696