Researcher Portfolio

Dr. Curdt, Werner

Department Sun and Heliosphere, Max Planck Institute for Solar System Research, Max Planck Society, MPI for Aeronomy, Max Planck Institute for Solar System Research, Max Planck Society

Researcher Profile

Position: Department Sun and Heliosphere, Max Planck Institute for Solar System Research, Max Planck Society

Position: MPI for Aeronomy, Max Planck Institute for Solar System Research, Max Planck Society

Researcher ID: https://pure.mpg.de/cone/persons/resource/persons103872

External references

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Publications

: Antoniadis, A., Gouleakis, T., Kleer, P., & Kolev, P. (2023). Secretary and Online Matching Problems with Machine Learned Advice. Discrete Optimization, 48(2): 100778. doi:10.1016/j.disopt.2023.100778. [PubMan] : Bonifaci, V., Facca, E., Folz, F., Karrenbauer, A., Kolev, P., Mehlhorn, K., Morigi, G., Shahkarami, G., & Vermande, Q. (2022). Physarum-inspired Multi-commodity Flow Dynamics. Theoretical Computer Science, 920, 1-20. doi:10.1016/j.tcs.2022.02.001. [PubMan] : Antoniadis, A., Gouleakis, T., Kleer, P., & Kolev, P. (2020). Secretary and Online Matching Problems with Machine Learned Advice. In H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, & H. Lin (Eds.), Advances in Neural Information Processing Systems 33 (pp. 7933-7944). Curran Associates, Inc. [PubMan] : Facca, E., Karrenbauer, A., Kolev, P., & Mehlhorn, K. (2020). Convergence of the Non-Uniform Directed Physarum Model. Theoretical Computer Science, 816, 184-194. doi:10.1016/j.tcs.2020.01.034. [PubMan] : Bonifaci, V., Facca, E., Folz, F., Karrenbauer, A., Kolev, P., Mehlhorn, K., Morigi, G., Shahkarami, G., & Vermande, Q. (2020). Physarum Multi-Commodity Flow Dynamics. Retrieved from https://arxiv.org/abs/2009.01498. [PubMan] : Karrenbauer, A., Kolev, P., & Mehlhorn, K. (2020). Convergence of the Non-Uniform Physarum Dynamics. Theoretical Computer Science, 816, 260-269. doi:10.1016/j.tcs.2020.02.032. [PubMan] : Antoniadis, A., Gouleakis, T., Kleer, P., & Kolev, P. (2020). Secretary and Online Matching Problems with Machine Learned Advice. Retrieved from https://arxiv.org/abs/2006.01026. [PubMan] : Ban, F., Bhattiprolu, V., Bringmann, K., Kolev, P., Lee, E., & Woodruff, D. (2019). A PTAS for l_p-Low Rank Approximation. In T. M. Chan (Ed.), Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms (pp. 747-766). Philadelphia, PA: SIAM. doi:10.1137/1.9781611975482.47. [PubMan] : Becker, R., Bonifaci, V., Karrenbauer, A., Kolev, P., & Mehlhorn, K. (2019). Two Results on Slime Mold Computations. Theoretical Computer Science, 773, 79-106. doi:10.1016/j.tcs.2018.08.027. [PubMan] : Facca, E., Karrenbauer, A., Kolev, P., & Mehlhorn, K. (2019). Convergence of the Non-Uniform Directed Physarum Model. Retrieved from http://arxiv.org/abs/1906.07781. [PubMan] : Karrenbauer, A., Kolev, P., & Mehlhorn, K. (2019). Convergence of the Non-Uniform Physarum Dynamics. Retrieved from http://arxiv.org/abs/1901.07231. [PubMan] : Kolev, P. (2018). Algorithmic Results for Clustering and Refined Physarum Analysis. PhD Thesis, Universität des Saarlandes, Saarbrücken. doi:10.22028/D291-27551. [PubMan] : Ban, F., Bhattiprolu, V., Bringmann, K., Kolev, P., Lee, E., & Woodruff, D. P. (2018). A PTAS for l p-Low Rank Approximation. Retrieved from http://arxiv.org/abs/1807.06101. [PubMan] : Jindal, G., Kolev, P., Peng, R., & Sawlani, S. (2017). Density Independent Algorithms for Sparsifying k-Step Random Walks. Retrieved from http://arxiv.org/abs/1702.06110. [PubMan] : Jindal, G., Kolev, P., Peng, R., & Sawlani, S. (2017). Density Independent Algorithms for Sparsifying k-Step Random Walks. In K. Jansen, J. D. P. Rolim, D. P. Williamson, & S. S. Vempala (Eds.), Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (pp. 1-17). Wadern: Schloss Dagstuhl. doi:10.4230/LIPIcs.APPROX-RANDOM.2017.14. [PubMan] : Becker, R., Bonifaci, V., Karrenbauer, A., Kolev, P., & Mehlhorn, K. (2017). Two Results on Slime Mold Computations. Retrieved from http://arxiv.org/abs/1707.06631. [PubMan] : Bringmann, K., Kolev, P., & Woodruff, D. (2017). Approximation Algorithms for l_0-Low Rank Approximation. In I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, & R. Garnett (Eds.), Advances in Neural Information Processing Systems 30 (pp. 6648-6659). Curran Associates. [PubMan] : Kolev, P., & Mehlhorn, K. (2016). A Note On Spectral Clustering. In P. Sankowski, & C. Zaroliagis (Eds.), 24th Annual European Symposium on Algorithms (pp. 1-14). Wadern: Schloss Dagstuhl. doi:10.4230/LIPIcs.ESA.2016.57. [PubMan] : Jindal, G., & Kolev, P. (2015). An Efficient Parallel Algorithm for Spectral Sparsification of Laplacian and SDDM Matrix Polynomials. Retrieved from http://arxiv.org/abs/1507.07497. [PubMan] : Kolev, P., & Mehlhorn, K. (2015). A Note On Spectral Clustering. Retrieved from http://arxiv.org/abs/1509.09188. [PubMan] : Kolev, P., & Sun, H. (2014). Dirichlet Eigenvalues, Local Random Walks, and Analyzing Clusters in Graphs. In H.-K. Ahn, & C.-S. Shin (Eds.), Algorithms and Computation (pp. 621-632). Berlin: Springer. doi:10.1007/978-3-319-13075-0_49. [PubMan] : Kolev, P. (2013). Community Analysis Using Local Random Walks. Master Thesis, Universität des Saarlandes, Saarbrücken. [PubMan]