Convex and Nonsmooth Optimization

First-Order Methods for Nonsmooth Nonconvex Functional Constrained Optimization with or without Slater Points

  • Zhichao Jia
  • Benjamin Grimmer
    • Categories Constrained Nonlinear Optimization, Nonsmooth Optimization Tags , , , ,

    Constrained optimization problems where both the objective and constraints may be nonsmooth and nonconvex arise across many learning and data science settings. In this paper, we show a simple first-order method finds a feasible, ϵ-stationary point at a convergence rate of O(ϵ−4) without relying on compactness or Constraint Qualification (CQ). When CQ holds, this convergence is measured by … Read more

    A New Inexact Proximal Linear Algorithm with Adaptive Stopping Criteria for Robust Phase Retrieval

  • Zhong Zheng
  • Shiqian Ma
  • Lingzhou Xue
    • Categories Nonlinear Optimization, Nonsmooth Optimization Tags , , , ,

    This paper considers the robust phase retrieval problem, which can be cast as a nonsmooth and nonconvex optimization problem. We propose a new inexact proximal linear algorithm with the subproblem being solved inexactly. Our contributions are two adaptive stopping criteria for the subproblem. The convergence behavior of the proposed methods is analyzed. Through experiments on … Read more

    A descent method for nonsmooth multiobjective optimization problems on Riemannian manifolds

  • Chunming Tang
  • Hao He
  • Jinbao Jian
  • Miantao Chao
    • Categories Constrained Nonlinear Optimization, Nonlinear Optimization, Nonsmooth Optimization Tags

    In this paper, a descent method for nonsmooth multiobjective optimization problems on complete Riemannian manifolds is proposed. The objective functions are only assumed to be locally Lipschitz continuous instead of convexity used in existing methods. A necessary condition for Pareto optimality in Euclidean space is generalized to the Riemannian setting. At every iteration, an acceptable … Read more

    The alternating simultaneous Halpern-Lions-Wittmann-Bauschke algorithm for finding the best approximation pair for two disjoint intersections of convex sets

  • Yair Censor
  • Rafiq Mansour
  • Daniel Reem
    • Categories Approximation Algorithms, Constrained Nonlinear Optimization, Convex Optimization Tags , , , , ,

    Given two nonempty and disjoint intersections of closed and convex subsets, we look for a best approximation pair relative to them, i.e., a pair of points, one in each intersection, attaining the minimum distance between the disjoint intersections. We propose an iterative process based on projections onto the subsets which generate the intersections. The process … Read more

    Numerical Methods for Convex Multistage Stochastic Optimization

  • Guanghui Lan
  • Alexander Shapiro
    • Categories Convex Optimization, Dynamic Programming, Stochastic Programming Tags , , , , , , ,

    \(\) Optimization problems involving sequential decisions in  a  stochastic environment    were studied  in  Stochastic Programming (SP), Stochastic Optimal Control  (SOC) and Markov Decision Processes (MDP). In this paper we mainly concentrate on SP and  SOC modelling   approaches. In these frameworks there are natural situations  when the considered problems are  convex. Classical approach to sequential … Read more

    On the B-differential of the componentwise minimum of two affine vector functions

  • Jean-Pierre Dussault
  • Jean Charles Gilbert
  • Baptiste Plaquevent-Jourdain
    • Categories Complementarity and Variational Inequalities, Convex and Nonsmooth Optimization, Nonsmooth Optimization Tags , , , , , , , , , , , , , , ,

    This paper focuses on the description and computation of the B-differential of the componentwise minimum of two affine vector functions. This issue arises in the reformulation of the linear complementarity problem with the Min C-function. The question has many equivalent formulations and we identify some of them in linear algebra, convex analysis and discrete geometry. … Read more

    Balancing Communication and Computation in Gradient Tracking Algorithms for Decentralized Optimization

  • Albert S. Berahas
  • Raghu Bollapragada
  • Shagun Gupta
    • Categories Convex Optimization, Nonlinear Optimization, Optimization in Data Science Tags , , , ,

    Gradient tracking methods have emerged as one of the most popular approaches for solving decentralized optimization problems over networks. In this setting, each node in the network has a portion of the global objective function, and the goal is to collectively optimize this function. At every iteration, gradient tracking methods perform two operations (steps): (1) … Read more

    Proximal bundle methods for hybrid weakly convex composite optimization problems

  • Jiaming Liang
  • Renato D.C. Monteiro
  • HonghaoZhang
    • Categories Nonlinear Optimization, Nonsmooth Optimization Tags , , , ,

    This paper establishes the iteration-complexity of proximal bundle methods for solving hybrid (i.e., a blend of smooth and nonsmooth) weakly convex composite optimization (HWC-CO) problems. This is done in a unified manner by considering a proximal bundle framework (PBF) based on a generic bundle update scheme which includes various well-known bundle update schemes. In contrast … Read more

    An Inexact Proximal-indefinite Stochastic ADMM with applications in 3D CT reconstruction

  • Jianchao Bai
    • Categories Convex Optimization, Stochastic Approaches Tags , , , , ,

    In this paper, we develop an Inexact Proximal-indefinite Stochastic ADMM (abbreviated as IPS-ADMM) for solving a class of separable convex optimization problems whose objective functions consist of two parts: one is an average of many smooth convex functions and another is a convex but possibly nonsmooth function. The involved smooth subproblem is tackled by an … Read more

    (ε-)Efficiency in Fractional Vector Optimization

  • Mounir El Maghri
    • Categories Convex and Nonsmooth Optimization, Global Optimization, Multi-Criteria Optimization Tags , , , ,

    The issue of characterizing completely efficient (Pareto) solutions to a fractional vector (multiobjective or multicriteria) minimization problem, where the involved functions are convex, has not been addressed previously. Thanks to an earlier characterization of weak efficiency in difference vector optimization by El Maghri, we get a vectorial necessary and sufficient condition given in terms of … Read more