prof. dr. Etienne de Klerk

Bio

Etienne de Klerk held assistant professorships at the TU Delft from 1998 to 2003, and from 2003 to 2005 an associate professorship at the University of Waterloo, Canada. In 2004 he was appointed at Tilburg University, first as associate professor, and then as full professor (2009). From August 2012 to August 2013, he was also appointed as full professor at the Nanyang Technological University in Singapore. From September 1st, 2015, to August 31st, 2019, he also held a part-time professorship at the TU Delft. He served five terms as associate editor of the SIAM Journal on Optimization, and has served two terms as associate editor of the INFORMS Journal Operations Research. He is co-recipient of the Canadian Foundation for Innovation’s New Opportunities Fund award, a recipient of the VIDI grant of the NWO, and co-recipient of the ENW-GROOT grant from the NWO. He received the 2017 Best Paper Prize from Optimization Letters for joint work on the complexity of gradient descent methods.

Expertise

My core expertise is mathematical optimization. For more details please see my personal homepage (with CV).

Courses

• Linear Optimization

Recent publications

1. Conditions for linear convergence of the gradient method for non-conv…

   Abbaszadehpeivasti, H., de Klerk, E., & Zamani, M. (Accepted/In press). Conditions for linear convergence of the gradient method for non-convex optimization. Optimization Letters. https://arxiv.org/abs/2204.00647

2. Convergence rate analysis of randomized and cyclic coordinate descent…

   Abbaszadehpeivasti, H., de Klerk, E., & Zamani, M. (Accepted/In press). Convergence rate analysis of randomized and cyclic coordinate descent for convex optimization through semidefinite programming. Applied Set-Valued Analysis and Optimization.

3. On the Rate of Convergence of the Difference-of-Convex Algorithm (DCA)

   Abbaszadehpeivasti, H., de Klerk, E., & Zamani, M. (2023). On the Rate of Convergence of the Difference-of-Convex Algorithm (DCA). Journal of Optimization Theory and Applications.

4. Revisiting semidefinite programming approaches to options pricing: Co…

   Henrion, D., Kirschner, F., de Klerk, E., Korda, M., Lasserre, J. B., & Magron, V. (2023). Revisiting semidefinite programming approaches to options pricing: Complexity and computational perspectives. INFORMS Journal on Computing, 35(2), 335-349. ,

5. The exact worst-case convergence rate of the gradient method with fix…

   Abbaszadehpeivasti, H., de Klerk, E., & Zamani, M. (2022). The exact worst-case convergence rate of the gradient method with fixed step lengths for L-smooth functions. Optimization Letters, 16(6), 1649–1661.