Extreme F-measure Maximization using Sparse Probability Estimates. - Kalina Jasinska; Krzysztof Dembczynski; Róbert Busa-Fekete; Karlson Pfannschmidt; Timo Klerx; Eyke Hüllermeier (ICML, 2016)

Evaluating Tests in Medical Diagnosis: Combining Machine Learning with Game-Theoretical Concepts. - Karlson Pfannschmidt; Eyke Hüllermeier; Susanne Held; Reto Neiger (IPMU (1), 2016)

Deep architectures for learning context-dependent ranking functions. - Karlson Pfannschmidt; Pritha Gupta; Eyke Hüllermeier (CoRR, 2018)

Learning Choice Functions. - Karlson Pfannschmidt; Pritha Gupta; Eyke Hüllermeier (CoRR, 2019)

Learning Choice Functions via Pareto-Embeddings. - Karlson Pfannschmidt; Eyke Hüllermeier (KI, 2020)

Learning context-dependent choice functions. - Karlson Pfannschmidt; Pritha Gupta; Björn Haddenhorst; Eyke Hüllermeier (Int. J. Approx. Reason., 2022)

A Prototype to Support Business Model Innovation through Crowdsourcing and Artificial Intelligence. - Arthur Klippenstein; Christoph Weskamp; Florian Laux; Florian Neuhaus; Karlson Pfannschmidt; Melissa Bülling; Stephan Kassanke (Wirtschaftsinformatik, 2023)

Efficient Time-Stepping for Numerical Integration Using Reinforcement Learning. - Michael Dellnitz; Eyke Hüllermeier; Marvin Lücke; Sina Ober-Blöbaum; Christian Offen; Sebastian Peitz; Karlson Pfannschmidt (SIAM J. Sci. Comput., 2023)