Research portal

  1. 2017
  2. On the worst-case complexity of the gradient method with exact line search for smooth strongly convex functions

    de Klerk, E., Glineur, F. & Taylor, A. Oct 2017 In : Optimization Letters. 11, 7, p. 1185–1199 15 p.

    Research output: Scientific - peer-reviewArticle

  3. Bound-constrained polynomial optimization using only elementary calculations

    de Klerk, E., Lasserre, J. B., Laurent, M. & Sun, Z. Aug 2017 In : Mathematics of Operations Research. 42, 3, p. 834-853

    Research output: Scientific - peer-reviewArticle

  4. Solving Sparse Polynomial Optimization Problems with Chordal Structure Using the Sparse, Bounded-Degree Sum-of-Squares Hierarchy

    Marandi, A., de Klerk, E. & Dahl, J. May 2017 Optimization Online

    Research output: Other research outputDiscussion paper

  5. Convergence analysis for Lasserre's measure-based hierarchy of upper bounds for polynomial optimization

    de Klerk, E., Laurent, M. & Sun, Z. Mar 2017 In : Mathematical Programming . 162, 1, p. 363-392

    Research output: Scientific - peer-reviewArticle

  6. On the convergence rate of grid search for polynomial optimization over the simplex

    de Klerk, E., Laurent, M., Sun, Z. & Vera Lizcano, J. Mar 2017 In : Optimization Letters. 11, 3, p. 597-608

    Research output: Scientific - peer-reviewArticle

  7. A numerical evaluation of the bounded degree sum-of-squares hierarchy of Lasserre, Toh, and Yang on the pooling problem

    Marandi, A., Dahl, J. & de Klerk, E. 3 Feb 2017 In : Annals of Operations Research. 22 p.

    Research output: Scientific - peer-reviewArticle

  8. Comparison of Lasserre's measure-based bounds for polynomial optimization to bounds obtained by simulated annealing

    de Klerk, E. & Laurent, M. 2017 In : Mathematics of Operations Research.

    Research output: Scientific - peer-reviewArticle

  9. Improved convergence rates for Lasserre-type hierarchies of upper bounds for box-constrained polynomial optimization

    de Klerk, E., Laurent, M. & Hess, R. 2017 In : SIAM Journal on Optimization. 27, 1, p. 346-367

    Research output: Scientific - peer-reviewArticle

  10. 2016
  11. On the Turing model complexity of interior point methods for semidefinite programming

    de Klerk, E. & Vallentin, F. Sep 2016 In : SIAM Journal on Optimization. 26, 3, p. 1944-1961

    Research output: Scientific - peer-reviewArticle

  12. On the Worst-Case Complexity of the Gradient Method with Exact Line Search for Smooth Strongly Convex Functions

    de Klerk, E., Glineur, F. & Taylor, A. 30 Jun 2016 Itacha: Cornell University Library, 10 p.(arXiv; vol. arXiv:1606.09365)

    Research output: Other research outputWorking paper

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