Giulia Ferrandi

Limited memory gradient methods for unconstrained optimization

  • Giulia Ferrandi
  • Michiel E. Hochstenbach
    • Categories Nonlinear Optimization, Unconstrained Optimization Tags , , , , ,

    The limited memory steepest descent method (Fletcher, 2012) for unconstrained optimization problems stores a few past gradients to compute multiple stepsizes at once. We review this method and propose new variants. For strictly convex quadratic objective functions, we study the numerical behavior of different techniques to compute new stepsizes. In particular, we introduce a method … Read more

    A harmonic framework for stepsize selection in gradient methods

  • Giulia Ferrandi
  • Michiel E. Hochstenbach
  • Nataša Krejić
    • Categories Nonlinear Optimization Tags , , , , ,

    We study the use of inverse harmonic Rayleigh quotients with target for the stepsize selection in gradient methods for nonlinear unconstrained optimization problems. This provides not only an elegant and flexible framework to parametrize and reinterpret existing stepsize schemes, but also gives inspiration for new flexible and tunable families of steplengths. In particular, we analyze … Read more