Sparse Multiple Kernel Learning: Alternating Best Response and Semidefinite Relaxations

  • Dimitris Bertsimas
  • Caio de Próspero Iglesias
  • Nicholas A. G. Johnson
    • Categories Convex Optimization, Semi-definite Programming, Statistics Tags , , , ,

    We study Sparse Multiple Kernel Learning (SMKL), which is the problem of selecting a sparse convex combination of prespecified kernels for support vector binary classification. Unlike prevailing \(\ell_1\)‐regularized approaches that approximate a sparsifying penalty, we formulate the problem by imposing an explicit cardinality constraint on the kernel weights and add an \(\ell_2\) penalty for robustness. … Read more

    Subgame Perfect Methods in Nonsmooth Convex Optimization

  • Benjamin Grimmer
  • Alex L. Wang
    • Categories Convex Optimization, Nonsmooth Optimization

    This paper considers nonsmooth convex optimization with either a subgradient or proximal operator oracle. In both settings, we identify algorithms that achieve the recently introduced game-theoretic optimality notion for algorithms known as subgame perfection. Subgame perfect algorithms meet a more stringent requirement than just minimax optimality. Not only must they provide optimal uniform guarantees on … Read more

    An Optimal Solution is Not Enough: Alternative Solutions and Optimal Power Systems

  • Matthew Viens
  • jkskolf
  • William E. Hart
  • Michael C. Ferris
    • Categories Applications - Science and Engineering, Energy, Optimization Software and Modeling Systems Tags , , , ,

    Power systems modeling and planning has long leveraged mathematical programming for its ability to provide optimality and feasibility guarantees. One feature that has been recognized in the optimization literature since the 1970s is the existence and meaning of multiple exact optimal and near-optimal solutions, which we call alternative solutions. In power systems modeling, the use … Read more

    Exact Decentralized Optimization via Explicit $\ell_1$ Consensus Penalties

  • Hong Wang
    • Categories Network Optimization, Nonlinear Optimization Tags ,

    Consensus optimization enables autonomous agents to solve joint tasks through peer-to-peer exchanges alone. Classical decentralized gradient descent is appealing for its minimal state but fails to achieve exact consensus with fixed stepsizes unless additional trackers or dual variables are introduced. We revisit penalty methods and introduce a decentralized two-layer framework that couples an outer penalty-continuation … Read more

    Dimensionality Reduction in Bilevel Linear Programming

  • Eneko C. Clemente
  • Oleg A. Prokopyev
    • Categories Bilevel Optimization, Combinatorial Optimization, Polyhedra Tags , ,

    We consider bilevel programs that involve a leader, who first commits to a mixed-integer decision, and a follower, who observes this decision and then responds rationally by solving a linear program (LP). Standard approaches often reformulate these bilevel optimization problems as single-level mixed-integer programs by exploiting the follower’s LP optimality conditions. These reformulations introduce either … Read more

    A Framework for Handling and Exploiting Symmetry in Benders’ Decomposition

  • Christopher Hojny
  • Cedric Roy
    • Categories (Mixed) Integer Linear Programming, Integer Programming, Scheduling Tags ,

    Benders’ decomposition (BD) is a framework for solving optimization problems by removing some variables and modeling their contribution to the original problem via so-called Benders cuts. While many advanced optimization techniques can be applied in a BD framework, one central technique has not been applied systematically in BD: symmetry handling. The main reason for this … Read more

    Complexity of quadratic penalty methods with adaptive accuracy under a PL condition for the constraints

  • Florentin Goyens
  • Geovani Nunes Grapiglia
    • Categories Constrained Nonlinear Optimization Tags , , ,

    We study the quadratic penalty method (QPM) for smooth nonconvex optimization problems with equality constraints. Assuming the constraint violation satisfies the PL condition near the feasible set, we derive sharper worst-case complexity bounds for obtaining approximate first-order KKT points. When the objective and constraints are twice continuously differentiable, we show that QPM equipped with a … Read more

    On Supportedness-Promoting Image Space Transformations in Multiobjective Optimization

  • Felix Neussel
  • Oliver Stein
    • Categories Multi-Criteria Optimization Tags , , , ,

    We study the supportedness of nondominated points of multiobjective optimization problems, that is, whether they can be obtained via weighted sum scalarization. One key question is how supported points behave under an efficiency-preserving transformation of the original problem. Under a differentiability assumption, we characterize the transformations that preserve both efficiency and supportedness as the component-wise … Read more

    A derivative-free trust-region approach for Low Order-Value Optimization problems

  • Francisco N. C. Sobral
  • A. E. Schwertner
    • Categories Constrained Nonlinear Optimization, Nonlinear Optimization Tags , , ,

    The Low Order-Value Optimization (LOVO) problem involves minimizing the minimum among a finite number of function values within a feasible set. LOVO has several practical applications such as robust parameter estimation, protein alignment, portfolio optimization, among others. In this work, we are interested in the constrained nonlinear optimization LOVO problem of minimizing the minimum between … Read more