An optimal subgradient algorithm with subspace search for costly convex optimization problems

  • Masoud Ahookhosh
  • Arnold Neumaier
    • Categories Convex and Nonsmooth Optimization, Convex Optimization, Nonsmooth Optimization Tags , , , , , , Short URL: https://optimization-online.org/?p=13362

    This paper presents an acceleration of the optimal subgradient algorithm OSGA \cite{NeuO} for solving convex optimization problems, where the objective function involves costly affine and cheap nonlinear terms. We combine OSGA with a multidimensional subspace search technique, which leads to low-dimensional problem that can be solved efficiently. Numerical results concerning some applications are reported. A software package implementing the new method is available.

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    Faculty of Mathematics, University of Vienna

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