Influence of Cruise Control on Driver Guidance - a Comparison between System Generations and Countries
N. Epple, S. Dari, L. Drees, V. Protschky, A. Riener, in: 2019 IEEE Intelligent Vehicles Symposium (IV), 2019.

Algorithm Selection as Recommendation: From Collaborative Filtering to Dyad Ranking
A. Tornede, M.D. Wever, E. Hüllermeier, in: F. Hoffmann, E. Hüllermeier, R. Mikut (Eds.), Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28. - 29. November 2019, KIT Scientific Publishing, Karlsruhe, 2019, pp. 135–146.

A Reduction of Label Ranking to Multiclass Classification
K. Brinker, E. Hüllermeier, in: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Würzburg, Germany, 2019.

Learning from Imprecise Data: Adjustments of Optimistic and Pessimistic Variants
E. Hüllermeier, I. Couso, S. Diestercke, in: Proceedings SUM 2019, International Conference on Scalable Uncertainty Management, 2019.

Mining Rank Data
S. Henzgen, E. Hüllermeier, ACM Transactions on Knowledge Discovery from Data (2019) 1–36.

Asymptotic confidence sets for the jump curve in bivariate regression problems
V. Bengs, M. Eulert, H. Holzmann, Journal of Multivariate Analysis (2019) 291–312.

Adaptive confidence sets for kink estimation
V. Bengs, H. Holzmann, Electronic Journal of Statistics (2019) 1523–1579.

From Automated to On-The-Fly Machine Learning
F. Mohr, M.D. Wever, A. Tornede, E. Hüllermeier, in: INFORMATIK 2019: 50 Jahre Gesellschaft Für Informatik – Informatik Für Gesellschaft, Gesellschaft für Informatik e.V., Bonn, 2019, pp. 273–274.

Automating Multi-Label Classification Extending ML-Plan
M.D. Wever, F. Mohr, A. Tornede, E. Hüllermeier, in: 2019.

Multimodal Turn-Taking: Motivations, Methodological Challenges, and Novel Approaches
K. Rohlfing, G. Leonardi, I. Nomikou, J. Rczaszek-Leonardi, E. Hüllermeier, IEEE Transactions on Cognitive and Developmental Systems (2019).