Publications

Michael Dellnitz, Eyke Hüllermeier, Marvin Lücke, Sina Ober-Blöbaum, Christian Offen, Sebastian Peitz, Karlson Pfannschmidt (2021). Efficient time stepping for numerical integration using reinforcement learning. arXiv.

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

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Karlson Pfannschmidt, Pritha Gupta, Eyke Hüllermeier (2019). Learning Choice Functions: Concepts and Architectures. CoRR.

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

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

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

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