Publications

Ricardo Knauer, and Erik Rodner. Cost-Sensitive Best Subset Selection for Logistic Regression: A Mixed-Integer Conic Optimization Perspective. KI 2023: Advances in Artificial Intelligence: 46th German Conference on AI, Berlin, Germany, September 26--29, 2023, Proceedings, 114--129, Springer-Verlag, Berlin, Heidelberg, 2023. [PUMA: best conic cost-sensitive interpretable learning machine meta-learning mixed-integer optimization selection subset zno]

P Kerschke, H Wang, M Preuss, C Grimme, A H Deutz, H Trautmann, and M T M Emmerich. Search dynamics on multimodal multiobjective problems. Evol. Comput., (27)4:577--609, MIT Press - Journals, 2019. [PUMA: Multiobjective analysis ascent gradient hypervolume landscape multimodality optimization set-based zno]

Fabian Gärtner, Christian Höner Zu Siederdissen, Lydia Müller, and Peter F Stadler. Coordinate systems for supergenomes. Algorithms Mol. Biol., (13)1:15, Springer Science and Business Media LLC, September 2018. [PUMA: Betweenness Big Colored Combinatorial Comparative Graph data genomics multigraph optimization ordering theory transcriptomics xack yaff]

Katja Hoffmann, Katja Cazemier, Christoph Baldow, Silvio Schuster, Yuri Kheifetz, Sibylle Schirm, Matthias Horn, Thomas Ernst, Constanze Volgmann, Christian Thiede, Andreas Hochhaus, Martin Bornhäuser, Meinolf Suttorp, Markus Scholz, Ingmar Glauche, Markus Loeffler, and Ingo Roeder. Integration of mathematical model predictions into routine workflows to support clinical decision making in haematology. BMC Med. Inform. Decis. Mak., (20)1:28, February 2020. [PUMA: Clinical Computer Haematology Individual Mathematical Model-based Routine Support decision-making management modelling optimization planning simulation system therapy treatment workflow zno data]

Pascal Kerschke, and Heike Trautmann. Automated algorithm selection on continuous black-box problems by combining Exploratory Landscape Analysis and machine learning. Evol. Comput., (27)1:99--127, MIT Press, 2019. [PUMA: algorithm analysis black-box continuous exploratory landscape learning machine optimization selection single-objective zno automated]