... to the web pages of the Computational Intelligence group. Our current research is focused on methodological foundations of computational intelligence, with a specific emphasis on machine learning and data mining as well as approximate reasoning and reasoning under uncertainty. Our vision and ambition is to develop methods that are both theoretically well-founded and effectively applicable, thereby bridging the gap between theoretical foundations and practical applications. In this regard, we are specifically interested in utilizing computational intelligence and machine learning methods in bioinformatics and the life sciences, but also in other domains such as engineering.
- ICCBR-2013 Best Paper Award: The paper "Preference-based CBR: A Search-based Problem Solving Framework" by Amira Abdel-Aziz, Weiwe Cheng, Marc Strickert and Eyke Hüllermeier received the Best Paper Award at ICCBR-2013, the 21st International Conference on Case-Based Reasoning.
- Honorable mentioning of our paper "On Label Dependence and Loss Minimization in Multi-label Classification" (Krzysztof Dembczynski, Willem Waegeman, Weiwei Cheng and Eyke Hüllermeier) in the list of notable computing items 2012 by the ACM.
- ECAI-2012 Best Paper Award: The paper "An Analysis
of Chaining in Multilabel Classification" by Krzysztof Dembczynski,
Willem Waegeman and Eyke Hüllermeier received the Best Paper Award at
ECAI-2012, the 20th European
Conference on Artificial Intelligence.