Wei Guo

R-Linear Convergence of Limited Memory Steepest Descent

  • Frank E. Curtis
  • Wei Guo
    • Categories Nonlinear Optimization, Unconstrained Optimization

    The limited memory steepest descent method (LMSD) proposed by Fletcher is an extension of the Barzilai-Borwein “two-point step size” strategy for steepest descent methods for solving unconstrained optimization problems. It is known that the Barzilai-Borwein strategy yields a method with an R-linear rate of convergence when it is employed to minimize a strongly convex quadratic. … Read more

    Handling Nonpositive Curvature in a Limited Memory Steepest Descent Method

  • Frank E. Curtis
  • Wei Guo
    • Categories Nonlinear Optimization, Unconstrained Optimization Tags , , , ,

    We propose a limited memory steepest descent (LMSD) method for solving unconstrained optimization problems. As a steepest descent method, the step computation in each iteration requires the evaluation of a gradient of the objective function and the calculation of a scalar step size only. When employed to solve certain convex problems, our method reduces to … Read more