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]
OmniOpt – A tool for hyperparameter optimization on HPC. In Heike Jagode, Hartwig Anzt, Hatem Ltaief, and Piotr Luszczek (Eds.), High Performance Computing - ISC High Performance Digital 2021 International Workshops, 2021, Revised Selected Papers, 285--296, Springer, Berlin u. a., Germany, Nov 13, 2021. [PUMA: FIS_scads High Hyperparameter computing networks neural optimization performance xack]
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]
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]
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]
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]