Convex and Nonsmooth Optimization

A new problem qualification based on approximate KKT conditions for Lipschitzian optimization with application to bilevel programming

  • Isabella Käming
  • Andreas Fischer
  • Alain Zemkoho
    • Categories Bilevel Optimization, Complementarity and Variational Inequalities, Nonsmooth Optimization

    When dealing with general Lipschitzian optimization problems, there are many problem classes where even weak constraint qualications fail at local minimizers. In contrast to a constraint qualification, a problem qualification does not only rely on the constraints but also on the objective function to guarantee that a local minimizer is a Karush-Kuhn-Tucker (KKT) point. For … Read more

    Relaxation methods for pessimistic bilevel optimization

  • Alain Zemkoho
    • Categories Bilevel Optimization, Complementarity and Variational Inequalities, Nonsmooth Optimization Tags , , , ,

    We consider a smooth pessimistic bilevel optimization problem, where the lower-level problem is convex and satisfies the Slater constraint qualification. These assumptions ensure that the Karush-Kuhn-Tucker (KKT) reformulation of our problem is well-defined. We then introduce and study the (i) Scholtes, (ii) Lin and Fukushima, (iii) Kadrani, Dussault and Benchakroun, (iv) Steffensen and Ulbrich, and … Read more

    Interior-point algorithms with full Newton steps for nonsymmetric convex conic optimization

  • Dávid Papp
  • Anita Varga
    • Categories Cone Programming, Convex Optimization Tags , , ,

    We design and analyze primal-dual, feasible interior-point algorithms (IPAs) employing full Newton steps to solve convex optimization problems in standard conic form. Unlike most nonsymmetric cone programming methods, the algorithms presented in this paper require only a logarithmically homogeneous self-concordant barrier (LHSCB) of the primal cone, but compute feasible and \(\varepsilon\)-optimal solutions to both the … Read more

    Provable and Practical Online Learning Rate Adaptation with Hypergradient Descent

  • Wenzhi Gao
    • Categories Convex Optimization, Nonlinear Optimization Tags

    This paper investigates the convergence properties of the hypergradient descent method (HDM), a 25-year-old heuristic originally proposed for adaptive stepsize selection in stochastic first-order methods. We provide the first rigorous convergence analysis of HDM using the online learning framework of [Gao24] and apply this analysis to develop new state-of-the-art adaptive gradient methods with empirical and … Read more

    Mean and variance estimation complexity in arbitrary distributions via Wasserstein minimization

  • Valentio Iverson
  • Stephen A. Vavasis
    • Categories Convex Optimization, Statistics Tags , , , ,

    Parameter estimation is a fundamental challenge in machine learning, crucial for tasks such as neural network weight fitting and Bayesian inference. This paper focuses on the complexity of estimating translation μ∈R^l and shrinkage σ∈R++ parameters for a distribution of the form (1/sigma^l) f_0((x−μ)/σ), where f_0 is a known density in R^l given n samples. We … Read more

    Convergence of Descent Optimization Algorithms under Polyak-Lojasiewicz-Kurdyka Conditions

  • Glaydston Bento
  • Boris S. Mordukhovich
  • Yurii Nesterov
  • Tiago Sousa Mota
    • Categories Nonsmooth Optimization, Unconstrained Optimization

    This paper develops a comprehensive convergence analysis for generic classes of descent algorithms in nonsmooth and nonconvex optimization under several conditions of the Polyak-Lojasiewicz-Kurdyka (PLK) type. Along other results, we prove the finite termination of generic algorithms under the PLK conditions with lower exponents. Specifications are given to establish new convergence rates for inexact reduced … Read more

    A necessary condition for the guarantee of the superiorization method

  • Kay Barshad
  • Yair Censor
  • Walaa M. Moursi
  • Tyler Weames
  • Henry Wolkowicz
    • Categories Biomedical Applications, Constrained Nonlinear Optimization, Convex Optimization Tags , , , , ,

    We study a method that involves principally convex feasibility-seeking and makes secondary efforts of objective function value reduction. This is the well-known superiorization method (SM), where the iterates of an asymptotically convergent iterative feasibility-seeking algorithm are perturbed by objective function nonascent steps. We investigate the question under what conditions a sequence generated by an SM … Read more

    Facial structure of copositive and completely positive cones over a second-order cone

  • Mitsuhiro Nishijima
  • Bruno F. Lourenço
    • Categories Convex and Nonsmooth Optimization, Linear, Cone and Semidefinite Programming Tags , , , , , ,

    We classify the faces of copositive and completely positive cones over a second-order cone and investigate their dimension and exposedness properties. Then we compute two parameters related to chains of faces of both cones. At the end, we discuss some possible extensions of the results with a view toward analyzing the facial structure of general … Read more

    Descent Scheme for a Class of Bilevel Programming Problems

  • Bhuvnesh Khatana
    • Categories Approximation Algorithms, Combinatorial Optimization, Complementarity and Variational Inequalities, Convex and Nonsmooth Optimization, Nonlinear Optimization Tags , , ,

    In this paper, a class of bilevel programming problems is studied, in which the lower level is a quadratic programming problem, and the upper level problem consists of a nonlinear objective function with coupling constraints. An iterative process is developed to generate a sequence of points, which converges to the solution of this problem. In … Read more

    Stable Set Polytopes with Rank |V(G)|/3 for the Lovász-Schrijver SDP Operator

  • Yu Hin (Gary) Au
    • Categories Combinatorial Optimization, Convex Optimization, Semi-definite Programming Tags , , , ,

    We study the lift-and-project rank of the stable set polytope of graphs with respect to the Lovász–Schrijver SDP operator \( \text{LS}_+ \) applied to the fractional stable set polytope. In particular, we show that for every positive integer \( \ell \), the smallest possible graph with \( \text{LS}_+ \)-rank \( \ell \) contains \( 3\ell … Read more