forward-backward algorithm

Convergence of Proximal Gradient Algorithm in the Presence of Adjoint Mismatch

  • Émilie Chouzenoux
  • Jean-Christophe Pesquet
  • Cyril Riddel
  • Marion Savanier
  • Yves Trousset
    • Categories Convex Optimization, Nonsmooth Optimization Tags , , , , , ,

    We consider the proximal gradient algorithm for solving penalized least-squares minimization problems arising in data science. This first-order algorithm is attractive due to its flexibility and minimal memory requirements allowing to tackle large-scale minimization problems involving non-smooth penalties. However, for problems such as X-ray computed tomography, the applicability of the algorithm is dominated by the … Read more

    On the linear convergence of the forward-backward splitting algorithm

  • Ba Khiet Le
    • Categories Convex and Nonsmooth Optimization Tags , , ,

    In this paper, we establish a linear convergence result for the forward-backward splitting algorithm in the finding a zero of the sum of two maximal monotone operators, where one of them is set-valued strongly monotone and the other is Lipschitz continuous. We show that our convergence rate is better than Douglas–Rachford splitting algorithm’s rate used … Read more

    A Proximal Interior Point Algorithm with Applications to Image Processing

  • Émilie Chouzenoux
  • Marie-Caroline Corbineau
  • Jean-Christophe Pesquet
    • Categories Constrained Nonlinear Optimization, Convex Optimization, Nonsmooth Optimization Tags , , , , , , , ,

    In this article, we introduce a new proximal interior point algorithm (PIPA). This algorithm is able to handle convex optimization problems involving various constraints where the objective function is the sum of a Lipschitz differentiable term and a possibly nonsmooth one. Each iteration of PIPA involves the minimization of a merit function evaluated for decaying … Read more

    On inexact relative-error hybrid proximal extragradient, forward-backward and Tseng’s modified forward-backward methods with inertial effects

  • M. Marques Alves
  • Raul T. Marcavillaca
    • Categories Convex and Nonsmooth Optimization Tags , , , , , , , ,

    In this paper, we propose and study the asymptotic convergence and nonasymptotic global convergence rates (iteration-complexity) of an inertial under-relaxed version of the relative-error hybrid proximal extragradient (HPE) method for solving monotone inclusion problems. We analyze the proposed method under more flexible assumptions than existing ones on the extrapolation and relative-error parameters. As applications, we … Read more

    Stochastic Approximations and Perturbations in Forward-Backward Splitting for Monotone Operators

  • Patrick L. Combettes
  • Jean-Christophe Pesquet
    • Categories Infinite Dimensional Optimization, Stochastic Programming Tags , , , , ,

    We investigate the asymptotic behavior of a stochastic version of the forward-backward splitting algorithm for finding a zero of the sum of a maximally monotone set-valued operator and a cocoercive operator in Hilbert spaces. Our general setting features stochastic approximations of the cocoercive operator and stochastic perturbations in the evaluation of the resolvents of the … Read more

    Stochastic Quasi-Fejér Block-Coordinate Fixed Point Iterations with Random Sweeping

  • Patrick L. Combettes
  • Jean-Christophe Pesquet
    • Categories Convex Optimization, Nonsmooth Optimization, Stochastic Programming Tags , , , , , , ,

    This work investigates the properties of stochastic quasi-Fejér monotone sequences in Hilbert spaces and emphasizes their pertinence in the study of the convergence of block-coordinate fixed point methods. The iterative methods under investigation feature random sweeping rules to select the blocks of variables that are activated over the course of the iterations and allow for … Read more

    Forward-Backward and Tseng’s Type Penalty Schemes for Monotone Inclusion Problems

  • Radu Ioan Bot
  • Ernö Robert Csetnek
    • Categories Convex Optimization Tags , , , , , , , ,

    We deal with monotone inclusion problems of the form $0\in Ax+Dx+N_C(x)$ in real Hilbert spaces, where $A$ is a maximally monotone operator, $D$ a cocoercive operator and $C$ the nonempty set of zeros of another cocoercive operator. We propose a forward-backward penalty algorithm for solving this problem which extends the one proposed by H. Attouch, … Read more

    Generalized Forward-Backward Splitting

  • Jalal Fadili
  • Hugo Raguet
  • Gabriel Peyré
    • Categories Convex Optimization, Nonsmooth Optimization Tags , , , , ,

    This paper introduces the generalized forward-backward splitting algorithm for minimizing convex functions of the form $F + \sum_{i=1}^n G_i$, where $F$ has a Lipschitz-continuous gradient and the $G_i$’s are simple in the sense that their Moreau proximity operators are easy to compute. While the forward-backward algorithm cannot deal with more than $n = 1$ non-smooth … Read more