Semi-definite Programming

A Survey of Recent Scalability Improvements for Semidefinite Programming with Applications in Machine Learning, Control, and Robotics

  • Amir Ali Ahmadi
  • Georgina Hall
  • Anirudha Majumdar
    • Categories Basic Sciences Applications, Control Applications, Semi-definite Programming Tags , , , ,

    Historically, scalability has been a major challenge to the successful application of semidefinite programming in fields such as machine learning, control, and robotics. In this paper, we survey recent approaches for addressing this challenge including (i) approaches for exploiting structure (e.g., sparsity and symmetry) in a problem, (ii) approaches that produce low-rank approximate solutions to … Read more

    Error Bounds and Singularity Degree in Semidefinite Programming

  • Stefan Sremac
  • Henry Wolkowicz
  • Hugo J. Woerdeman
    • Categories Convex Optimization, Semi-definite Programming Tags , , ,

    In semidefinite programming a proposed optimal solution may be quite poor in spite of having sufficiently small residual in the optimality conditions. This issue may be framed in terms of the discrepancy between forward error (the unmeasurable `true error’) and backward error (the measurable violation of optimality conditions). In his seminal work, Sturm provided an … Read more

    A convex relaxation to compute the nearest structured rank deficient matrix

  • Diego Cifuentes
    • Categories Semi-definite Programming Tags , , ,

    Given an affine space of matrices L and a matrix \theta in L, consider the problem of finding the closest rank deficient matrix to \theta on L with respect to the Frobenius norm. This is a nonconvex problem with several applications in estimation problems. We introduce a novel semidefinite programming (SDP) relaxation, and we show … Read more

    Burer-Monteiro guarantees for general semidefinite programs

  • Diego Cifuentes
    • Categories Semi-definite Programming Tags , , ,

    Consider a semidefinite program (SDP) involving an $n\times n$ positive semidefinite matrix $X$. The Burer-Monteiro method consists in solving a nonconvex program in $Y$, where $Y$ is an $n\times p$ matrix such that $X = Y Y^T$. Despite nonconvexity, Boumal et al. showed that the method provably solves generic equality-constrained SDP’s when $p > \sqrt{2m}$, … Read more

    Lower Bounds for the Bandwidth Problem

  • Truden Christian
  • Franz Rendl
  • Renata Sotirov
    • Categories Semi-definite Programming Tags , ,

    The Bandwidth Problem asks for a simultaneous permutation of the rows and columns of the adjacency matrix of a graph such that all nonzero entries are as close as possible to the main diagonal. This work focuses on investigating novel approaches to obtain lower bounds for the bandwidth problem. In particular, we use vertex partitions … Read more

    Noisy Euclidean Distance Matrix Completion with a Single Missing Node

  • Lucas Pettersson
  • Stefan Sremac
  • Henry Wolkowicz
  • Fei Wang
    • Categories Convex Optimization, Semi-definite Programming, Telecommunications Tags , , , , , ,

    We present several solution techniques for the noisy single source localization problem, i.e.,~the Euclidean distance matrix completion problem with a single missing node to locate under noisy data. For the case that the sensor locations are fixed, we show that this problem is implicitly convex, and we provide a purification algorithm along with the SDP … Read more

    Tractable semi-algebraic approximation using Christoffel-Darboux kernel

  • Didier Henrion
  • Jean-Bernard Lasserre
  • Swann Marx
  • Edouard Pauwels
  • Tillmann Weisser
    • Categories Semi-definite Programming Tags , , , ,

    We provide a new method to approximate a (possibly discontinuous) function using Christoffel-Darboux kernels. Our knowledge about the unknown multivariate function is in terms of finitely many moments of the Young measure supported on the graph of the function. Such an input is available when approximating weak (or measure-valued) solution of optimal control problems, entropy … Read more

    An Augmented Lagrangian algorithm for nonlinear semidefinite programming applied to the covering problem

  • Ernesto G. Birgin
  • Walter Gómez
  • Gabriel Haeser
  • Leonardo M. Mito
  • Daiana O. Santos
    • Categories Constrained Nonlinear Optimization, Convex Optimization, Semi-definite Programming Tags , , ,

    In this work we present an Augmented Lagrangian algorithm for nonlinear semidefinite problems (NLSDPs), which is a natural extension of its consolidated counterpart in nonlinear programming. This method works with two levels of constraints; one that is penalized and other that is kept within the subproblems. This is done in order to allow exploiting the … Read more

    CONICOPF: Conic relaxations for AC optimal power flow computations

  • Christian Bingane
  • Miguel F. Anjos
  • Sébastien Le Digabel
    • Categories Semi-definite Programming Tags , , ,

    Computational speed and global optimality are key needs for practical algorithms for the optimal power flow problem. Two convex relaxations offer a favorable trade-off between the standard second-order cone and the standard semidefinite relaxations for large-scale meshed networks in terms of optimality gap and computation time: the tight-and-cheap relaxation (TCR) and the quadratic convex relaxation … Read more

    Doubly nonnegative relaxations are equivalent to completely positive reformulations of quadratic optimization problems with block-clique graph structures

  • Sunyoung Kim
  • Masakazu Kojima
  • Kim-Chuan Toh
    • Categories Linear, Cone and Semidefinite Programming, Semi-definite Programming Tags , , , , ,

    We study the equivalence among a nonconvex QOP, its CPP and DNN relaxations under the assumption that the aggregated and correlative sparsity of the data matrices of the CPP relaxation is represented by a block-clique graph $G$. By exploiting the correlative sparsity, we decompose the CPP relaxation problem into a clique-tree structured family of smaller … Read more