Dr. J. (Jannis) Kurtz
Assistant Professor in Mathematical Methods and Applications in Data Science
Faculty of Economics and Business
Section Business Analytics
Visiting address
- Plantage Muidergracht 12
Postal address
- Postbus 15953
1001 NL Amsterdam
Contact details
Social media
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Publications
2023
- Goerigk, M., & Kurtz, J. (2023). Data-Driven Robust Optimization using Unsupervised Deep Learning. Computers & Operations Research, 151, [106087]. https://doi.org/10.1016/j.cor.2022.106087 [details]
2021
- Bah, B., Kurtz, J., & Schaudt, O. (2021). Discrete optimization methods for group model selection in compressed sensing. Mathematical programming, 190(1-2), 171-220. https://doi.org/10.1007/s10107-020-01529-7
2020
- Eufinger, L., Kurtz, J., Buchheim, C., & Clausen, U. (2020). A Robust Approach to the Capacitated Vehicle Routing Problem with Uncertain Costs. INFORMS Journal on Optimization, 2(2), 79-95. https://doi.org/10.1287/ijoo.2019.0021
- Goerigk, M., Kurtz, J., & Poss, M. (2020). Min–max–min robustness for combinatorial problems with discrete budgeted uncertainty. Discrete Applied Mathematics, 285, 707-725. https://doi.org/10.1016/j.dam.2020.07.011
- Kaemmerling, N., & Kurtz, J. (2020). Oracle-based algorithms for binary two-stage robust optimization. COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, 77(2), 539-569. https://doi.org/10.1007/s10589-020-00207-w
2019
- Chassein, A., Goerigk, M., Kurtz, J., & Poss, M. (2019). Faster algorithms for min-max-min robustness for combinatorial problems with budgeted uncertainty. European Journal of Operational Research, 279(2), 308-319. https://doi.org/10.1016/j.ejor.2019.05.045
2018
- Buchheim, C., & Kurtz, J. (2018). Complexity of min–max–min robustness for combinatorial optimization under discrete uncertainty. Discrete Optimization, 28, 1-15. https://doi.org/10.1016/j.disopt.2017.08.006
- Buchheim, C., & Kurtz, J. (2018). Robust combinatorial optimization under convex and discrete cost uncertainty. EURO Journal on Computational Optimization, 6(3), 211-238. https://doi.org/10.1007/s13675-018-0103-0
- Kurtz, J. (2018). Robust combinatorial optimization under budgeted-ellipsoidal uncertainty. EURO Journal on Computational Optimization, 6(4), 315-337. https://doi.org/10.1007/s13675-018-0097-7
2017
- Buchheim, C., & Kurtz, J. (2017). Min–max–min robust combinatorial optimization. Mathematical programming, 163(1-2), 1-23. https://doi.org/10.1007/s10107-016-1053-z
2016
- Buchheim, C., & Kurtz, J. (2016). Min-max-min robustness: A new approach to combinatorial optimization under uncertainty based on multiple solutions. Electronic Notes in Discrete Mathematics, 52, 45-52. https://doi.org/10.1016/j.endm.2016.03.007
2014
- Kawohl, B., Kroemer, S., & Kurtz, J. (2014). Radial Eigenfunctions for the Game-Theoretic p-Laplacian on a Ball. DIFFERENTIAL AND INTEGRAL EQUATIONS, 27(7-8), 659-670.
2022
Kurtz, J. (2022). Ensemble Methods for Robust Support Vector Machines using Integer Programming. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.2203.01606 [details]
2021
- Kurtz, J. (2021). New complexity results and algorithms for min-max-min robust combinatorial optimization. ArXiv. https://doi.org/10.48550/arXiv.2106.03107
- Kurtz, J., & Bah, B. (2021). Efficient and Robust Mixed-Integer Optimization Methods for Training Binarized Deep Neural Networks. ArXiv. https://doi.org/10.48550/arXiv.2110.11382
2020
- Bah, B., & Kurtz, J. (2020). An integer programming approach to deep neural networks with binary activation functions. (v3 ed.) ArXiv. https://doi.org/10.48550/arXiv.2007.03326
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Ancillary activities
No ancillary activities
Kurtz, J. (2022). Ensemble Methods for Robust Support Vector Machines using Integer Programming. (v1 ed.) ArXiv.