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On the convergence of the iterates of the “fast iterative shrinkage/thresholding algorithm”. (English) Zbl 1371.65047
Summary: We discuss here the convergence of the iterates of the “Fast Iterative Shrinkage/Thresholding Algorithm”, which is an algorithm proposed by A. Beck and M. Teboulle [SIAM J. Imaging Sci. 2, No. 1, 183–202 (2009; Zbl 1175.94009)] for minimizing the sum of two convex, lower-semicontinuous, and proper functions (defined in a Euclidean or Hilbert space), such that one is differentiable with Lipschitz gradient, and the proximity operator of the second is easy to compute. It builds a sequence of iterates for which the objective is controlled, up to a (nearly optimal) constant, by the inverse of the square of the iteration number. However, the convergence of the iterates themselves is not known. We show here that with a small modification, we can ensure the same upper bound for the decay of the energy, as well as the convergence of the iterates to a minimizer.

65J15 Numerical solutions to equations with nonlinear operators
65Y20 Complexity and performance of numerical algorithms
90C25 Convex programming
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