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439 Publications
2019 | Conference Paper | LibreCat-ID: 15007 | 
Learning to Aggregate: Tackling the Aggregation/Disaggregation Problem for OWA
V. Melnikov, E. Hüllermeier, in: Proceedings ACML, Asian Conference on Machine Learning (Proceedings of Machine Learning Research, 101), 2019.
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V. Melnikov, E. Hüllermeier, in: Proceedings ACML, Asian Conference on Machine Learning (Proceedings of Machine Learning Research, 101), 2019.
2019 | Conference Paper | LibreCat-ID: 15011 |
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.
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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.
2019 | Conference Paper | LibreCat-ID: 15013
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.
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K. Brinker, E. Hüllermeier, in: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Würzburg, Germany, 2019.
2019 | Conference Paper | LibreCat-ID: 15014
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.
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E. Hüllermeier, I. Couso, S. Diestercke, in: Proceedings SUM 2019, International Conference on Scalable Uncertainty Management, 2019.
2019 | Journal Article | LibreCat-ID: 15015
Mining Rank Data
S. Henzgen, E. Hüllermeier, ACM Transactions on Knowledge Discovery from Data (2019) 1–36.
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S. Henzgen, E. Hüllermeier, ACM Transactions on Knowledge Discovery from Data (2019) 1–36.
2019 | Conference Abstract | LibreCat-ID: 13132
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.
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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.
2019 | Conference Paper | LibreCat-ID: 10232 |
Automating Multi-Label Classification Extending ML-Plan
M.D. Wever, F. Mohr, A. Tornede, E. Hüllermeier, in: 2019.
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M.D. Wever, F. Mohr, A. Tornede, E. Hüllermeier, in: 2019.
2019 | Journal Article | LibreCat-ID: 20243
Multimodal Turn-Taking: Motivations, Methodological Challenges, and Novel Approaches
K. Rohlfing, G. Leonardi, I. Nomikou, J. Rączaszek-Leonardi, E. Hüllermeier, IEEE Transactions on Cognitive and Developmental Systems (2019).
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K. Rohlfing, G. Leonardi, I. Nomikou, J. Rączaszek-Leonardi, E. Hüllermeier, IEEE Transactions on Cognitive and Developmental Systems (2019).
2018 | Conference Paper | LibreCat-ID: 2479 |
(WIP) Towards the Automated Composition of Machine Learning Services
F. Mohr, M.D. Wever, E. Hüllermeier, A. Faez, in: SCC, IEEE, San Francisco, CA, USA, 2018.
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F. Mohr, M.D. Wever, E. Hüllermeier, A. Faez, in: SCC, IEEE, San Francisco, CA, USA, 2018.
2018 | Conference Paper | LibreCat-ID: 2857 |
Programmatic Task Network Planning
F. Mohr, T. Lettmann, E. Hüllermeier, M.D. Wever, in: Proceedings of the 1st ICAPS Workshop on Hierarchical Planning, AAAI, 2018, pp. 31–39.
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F. Mohr, T. Lettmann, E. Hüllermeier, M.D. Wever, in: Proceedings of the 1st ICAPS Workshop on Hierarchical Planning, AAAI, 2018, pp. 31–39.
2018 | Conference Paper | LibreCat-ID: 2471 |
On-The-Fly Service Construction with Prototypes
F. Mohr, M.D. Wever, E. Hüllermeier, in: SCC, IEEE Computer Society, San Francisco, CA, USA, 2018.
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F. Mohr, M.D. Wever, E. Hüllermeier, in: SCC, IEEE Computer Society, San Francisco, CA, USA, 2018.
2018 | Journal Article | LibreCat-ID: 3402
On the effectiveness of heuristics for learning nested dichotomies: an empirical analysis
V. Melnikov, E. Hüllermeier, Machine Learning (2018).
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V. Melnikov, E. Hüllermeier, Machine Learning (2018).
2018 | Journal Article | LibreCat-ID: 3510 |
ML-Plan: Automated Machine Learning via Hierarchical Planning
F. Mohr, M.D. Wever, E. Hüllermeier, Machine Learning (2018) 1495–1515.
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F. Mohr, M.D. Wever, E. Hüllermeier, Machine Learning (2018) 1495–1515.
2018 | Conference Paper | LibreCat-ID: 3552 |
Reduction Stumps for Multi-Class Classification
F. Mohr, M.D. Wever, E. Hüllermeier, in: Proceedings of the Symposium on Intelligent Data Analysis, ‘s-Hertogenbosch, the Netherlands, n.d.
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F. Mohr, M.D. Wever, E. Hüllermeier, in: Proceedings of the Symposium on Intelligent Data Analysis, ‘s-Hertogenbosch, the Netherlands, n.d.
2018 | Conference Paper | LibreCat-ID: 3852 |
ML-Plan for Unlimited-Length Machine Learning Pipelines
M.D. Wever, F. Mohr, E. Hüllermeier, in: ICML 2018 AutoML Workshop, 2018.
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M.D. Wever, F. Mohr, E. Hüllermeier, in: ICML 2018 AutoML Workshop, 2018.
2018 | Conference Paper | LibreCat-ID: 2109 |
Ensembles of Evolved Nested Dichotomies for Classification
M.D. Wever, F. Mohr, E. Hüllermeier, in: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018, ACM, Kyoto, Japan, 2018.
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M.D. Wever, F. Mohr, E. Hüllermeier, in: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018, ACM, Kyoto, Japan, 2018.
2018 | Preprint | LibreCat-ID: 17713 |
Automated Multi-Label Classification based on ML-Plan
M.D. Wever, F. Mohr, E. Hüllermeier, (2018).
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M.D. Wever, F. Mohr, E. Hüllermeier, (2018).
2018 | Preprint | LibreCat-ID: 17714 |
Automated machine learning service composition
F. Mohr, M.D. Wever, E. Hüllermeier, (2018).
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F. Mohr, M.D. Wever, E. Hüllermeier, (2018).
2018 | Book Chapter | LibreCat-ID: 6423
Preference-Based Reinforcement Learning Using Dyad Ranking
D. Schäfer, E. Hüllermeier, in: Discovery Science, Springer International Publishing, Cham, 2018, pp. 161–175.
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D. Schäfer, E. Hüllermeier, in: Discovery Science, Springer International Publishing, Cham, 2018, pp. 161–175.
2018 | Conference (Editor) | LibreCat-ID: 10591
Research Directions for Principles of Data Management
S. Abiteboul, M. Arenas, P. Barceló, M. Bienvenu, D. Calvanese, C. David, R. Hull, E. Hüllermeier, B. Kimelfeld, L. Libkin, W. Martens, T. Milo, F. Murlak, F. Neven, M. Ortiz, T. Schwentick, J. Stoyanovich, J. Su, D. Suciu, V. Vianu, K. Yi, eds., Research Directions for Principles of Data Management, 2018.
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S. Abiteboul, M. Arenas, P. Barceló, M. Bienvenu, D. Calvanese, C. David, R. Hull, E. Hüllermeier, B. Kimelfeld, L. Libkin, W. Martens, T. Milo, F. Murlak, F. Neven, M. Ortiz, T. Schwentick, J. Stoyanovich, J. Su, D. Suciu, V. Vianu, K. Yi, eds., Research Directions for Principles of Data Management, 2018.