Ives Macêdo

Low-rank spectral optimization

  • Michael P. Friedlander
  • Ives Macêdo
    • Categories Convex Optimization

    Various applications in signal processing and machine learning give rise to highly structured spectral optimization problems characterized by low-rank solutions. Two important examples that motivate this work are optimization problems from phase retrieval and from blind deconvolution, which are designed to yield rank-1 solutions. An algorithm is described based solving a certain constrained eigenvalue optimization … Read more

    Gauge optimization, duality, and applications

  • Michael P. Friedlander
  • Ives Macêdo
  • Ting Kei Pong
    • Categories Convex Optimization Tags , , ,

    Gauge functions significantly generalize the notion of a norm, and gauge optimization, as defined by Freund (1987), seeks the element of a convex set that is minimal with respect to a gauge function. This conceptually simple problem can be used to model a remarkable array of useful problems, including a special case of conic optimization, … Read more