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  • Etienne de Klerk
2016

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: Contribution to journalArticleScientificpeer-review

2019

Distributionally robust optimization with polynomial densities: Theory, models and algorithms

de Klerk, E., Kuhn, D. & Postek, K. S., Sep 2019, In : Mathematical Programming .

Research output: Contribution to journalArticleScientificpeer-review

16 Downloads (Pure)
2020

Solving sparse polynomial optimization problems with chordal structure using the sparse bounded-degree sum-of-squares hierarchy

de Klerk, E., Marandi, A. & Dahl, J., Mar 2020, In : Discrete Applied Mathematics. 275, p. 95-110

Research output: Contribution to journalArticleScientificpeer-review

2016

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: Working paperOther research output

Computer-assisted proofs and semidefinite programming

de Klerk, E., May 2016, In : Optima: Mathematical Optimization Society Newsletter. 100, p. 11-11 1 p.

Research output: Contribution to journalBook/Film/Article reviewOther research output

2020

Worst-case examples for Lasserre's measure-based hierarchy for polynomial optimization on the hypercube

de Klerk, E. & Laurent, M., 2020, In : Mathematics of Operations Research. 45, 1, p. 86-98

Research output: Contribution to journalArticleScientificpeer-review

Open Access
File
19 Downloads (Pure)
2019

A survey of semidefinite programming approaches to the generalized problem of moments and their error analysis

de Klerk, E. & Laurent, M., Dec 2019, World Women in Mathematics 2018: Proceedings of the First World Meeting for Women in Mathematics (WM)². Araujo, C., Benkart, G., Praeger, C. E. & Tanbay, B. (eds.). Cham: Springer, p. 17-56 (Association for Women in Mathematics Series ; vol. 20).

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

Open Access
File
21 Downloads (Pure)
2017

Comparison of Lasserre's Measure-based Bounds for Polynomial Optimization to Bounds Obtained by Simulated Annealing

de Klerk, E. & Laurent, M., Mar 2017, Ithaca: Cornell University Library, 12 p. (arXiv; vol. 1703.00744).

Research output: Working paperOther research output

Open Access
File
14 Downloads (Pure)

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: Working paperDiscussion paperOther research output

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: Contribution to journalArticleScientificpeer-review

Open Access
File
87 Downloads (Pure)
2018

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

de Klerk, E. & Laurent, M., Nov 2018, In : Mathematics of Operations Research. 43, 4, p. 1317-1325

Research output: Contribution to journalArticleScientificpeer-review

File
80 Downloads (Pure)
2017

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: Contribution to journalArticleScientificpeer-review

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

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

Research output: Contribution to journalArticleScientificpeer-review

Open Access
File
46 Downloads (Pure)
2016

[Review of the book An Introduction to Polynomial and Semi-Algebraic Optimization, Jean-Bernard Lasserre, 2015]

de Klerk, E., 2016, In : European Journal of Operational Research. 249, 2, p. 789-790 2 p.

Research output: Contribution to journalBook/Film/Article reviewOther research output

2020

Convergence analysis of a Lasserre hierarchy of upper bounds for polynomial minimization on the sphere

de Klerk, E. & Laurent, M., Jan 2020, In : Mathematical Programming .

Research output: Contribution to journalArticleScientificpeer-review

Open Access
2017

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: Contribution to journalArticleScientificpeer-review

2016

Improved Convergence Rates for Lasserre-type Hierarchies of Upper Bounds for Box-Constrained Polynomial Optimization

de Klerk, E., Laurent, M. & Hess, R., 16 Mar 2016, Ithaca: Cornell University Library, 21 p. (arXiv; vol. 1603.03329).

Research output: Working paperOther research output

Open Access
2017

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: Contribution to journalArticleScientificpeer-review

2018

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., Jun 2018, In : Annals of Operations Research. 265, 1, p. 67-92

Research output: Contribution to journalArticleScientificpeer-review

Open Access
File
126 Downloads (Pure)
2019

Polynomial norms

Ahmadi, A., de Klerk, E. & Hall, G., 2019, In : SIAM Journal on Optimization. 29, 1, p. 399–422

Research output: Contribution to journalArticleScientificpeer-review

Open Access
File
19 Downloads (Pure)