Convex and Nonsmooth Optimization

An Improved Method of Total Variation Superiorization Applied to Reconstruction in Proton Computed Tomography

  • Yair Censor
  • Paniz Karbasi
  • Keith E. Schubert
  • Reinhard W. Schulte
  • Blake Schultze
    • Categories Biomedical Applications, Constrained Nonlinear Optimization, Convex Optimization Tags , , , , ,

    Previous work showed that total variation superiorization (TVS) improves reconstructed image quality in proton computed tomography (pCT). The structure of the TVS algorithm has evolved since then and this work investigated if this new algorithmic structure provides additional benefits to pCT image quality. Structural and parametric changes introduced to the original TVS algorithm included: (1) … Read more

    Inexact Successive Quadratic Approximation for Regularized Optimization

  • Stephen Wright
  • Ching-pei Lee
    • Categories Nonlinear Optimization, Nonsmooth Optimization Tags , , , , , ,

    Successive quadratic approximations, or second-order proximal methods, are useful for minimizing functions that are a sum of a smooth part and a convex, possibly nonsmooth part that promotes regularization. Most analyses of iteration complexity focus on the special case of proximal gradient method, or accelerated variants thereof. There have been only a few studies of … Read more

    A Simple Nearly-Optimal Restart Scheme For Speeding-Up First-Order Methods

  • Benjamin Grimmer
  • James Renegar
    • Categories Convex Optimization, Nonsmooth Optimization Tags , ,

    We present a simple scheme for restarting first-order methods for convex optimization problems. Restarts are made based only on achieving specified decreases in objective values, the specified amounts being the same for all optimization problems. Unlike existing restart schemes, the scheme makes no attempt to learn parameter values characterizing the structure of an optimization problem, … Read more

    ADMM for Multiaffine Constrained Optimization

  • Frank E. Curtis
  • Wenbo Gao
  • Donald Goldfarb
    • Categories Constrained Nonlinear Optimization, Nonsmooth Optimization Tags , , , ,

    We propose an expansion of the scope of the alternating direction method of multipliers (ADMM). Specifically, we show that ADMM, when employed to solve problems with multiaffine constraints that satisfy certain easily verifiable assumptions, converges to the set of constrained stationary points if the penalty parameter in the augmented Lagrangian is sufficiently large. When the … Read more

    Algorithms and Convergence Results of Projection Methods for Inconsistent Feasibility Problems: A Review

  • Yair Censor
  • Maroun Zaknoon
    • Categories Convex Optimization, Nonlinear Optimization Tags , ,

    The convex feasibility problem (CFP) is to find a feasible point in the intersection of finitely many convex and closed sets. If the intersection is empty then the CFP is inconsistent and a feasible point does not exist. However, algorithmic research of inconsistent CFPs exists and is mainly focused on two directions. One is oriented … Read more

    Uniqueness of DRS as the 2 Operator Resolvent-Splitting and Impossibility of 3 Operator Resolvent-Splitting

  • Ernest K. Ryu
    • Categories Convex Optimization

    Given the success of Douglas-Rachford splitting (DRS), it is natural to ask whether DRS can be generalized. Are there are other 2 operator splittings? Can DRS be generalized to 3 operators? This work presents the answers: no and no. In a certain sense, DRS is the unique 2 operator resolvent-splitting, and generalizing DRS to 3 … Read more

    A Progressive Batching L-BFGS Method for Machine Learning

  • Raghu Bollapragada
  • Jorge Nocedal
  • Hao-Jun Shi
  • Ping Tak Peter Tang
  • Dheevatsa Mudigere
    • Categories Convex Optimization, Nonlinear Optimization, Stochastic Programming Tags , , ,

    The standard L-BFGS method relies on gradient approximations that are not dominated by noise, so that search directions are descent directions, the line search is reliable, and quasi-Newton updating yields useful quadratic models of the objective function. All of this appears to call for a full batch approach, but since small batch sizes give rise … Read more

    Pointed Closed Convex Sets are the Intersection of All Rational Supporting Closed Halfspaces

  • Marcel K. de Carli Silva
  • Levent Tunçel
    • Categories Convex and Nonsmooth Optimization, Integer Programming Tags ,

    We prove that every pointed closed convex set in $\mathbb{R}^n$ is the intersection of all the rational closed halfspaces that contain it. This generalizes a previous result by the authors for compact convex sets. CitationarXiv:1802.03296. February 2018ArticleDownload View PDF

    Cut-Pursuit Algorithm for Regularizing Nonsmooth Functionals with Graph Total Variation

  • Landrieu Loïc
  • Hugo Raguet
    • Categories Biomedical Applications, Data-Mining, Nonsmooth Optimization

    We present an extension of the cut-pursuit algorithm, introduced by Landrieu and Obozinski (2017), to the graph total-variation regularization of functions with a separable nondifferentiable part. We propose a modified algorithmic scheme as well as adapted proofs of convergence. We also present a heuristic approach for handling the cases in which the values associated to … Read more