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440 Publications


2022 | Conference Paper | LibreCat-ID: 34542
Scikit-Weak: A Python Library for Weakly Supervised Machine Learning
A. Campagner, J. Lienen, E. Hüllermeier, D. Ciucci, in: Lecture Notes in Computer Science, Springer, 2022, pp. 57–70.
LibreCat
 

2022 | Preprint | LibreCat-ID: 31546 | OA
Conformal Credal Self-Supervised Learning
J. Lienen, C. Demir, E. Hüllermeier, ArXiv:2205.15239 (2022).
LibreCat | Download (ext.)
 

2022 | Preprint | LibreCat-ID: 30867
Machine Learning for Online Algorithm Selection under Censored Feedback
A. Tornede, V. Bengs, E. Hüllermeier, Proceedings of the 36th AAAI Conference on Artificial Intelligence (2022).
LibreCat | arXiv
 

2022 | Preprint | LibreCat-ID: 30865
Algorithm Selection on a Meta Level
A. Tornede, L. Gehring, T. Tornede, M.D. Wever, E. Hüllermeier, Machine Learning (2022).
LibreCat | arXiv
 

2022 | Journal Article | LibreCat-ID: 33090
A comparison of heuristic, statistical, and machine learning methods for heated tool butt welding of two different materials
K. Gevers, A. Tornede, M.D. Wever, V. Schöppner, E. Hüllermeier, Welding in the World (2022).
LibreCat | DOI
 

2022 | Report | LibreCat-ID: 36227
Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten mittels Maschinellen Lernens
B. Hammer, E. Hüllermeier, V. Lohweg, A. Schneider, W. Schenck, U. Kuhl, M. Braun, A. Pfeifer, C.-A. Holst, M. Schmidt, G. Schomaker, T. Tornede, Schlussbericht ITS.ML: Intelligente Technische Systeme der nächsten Generation durch Maschinelles Lernen. Forschungsvorhaben zur automatisierten Analyse von Daten mittels Maschinellen Lernens, 2022.
LibreCat | DOI
 

2022 | Journal Article | LibreCat-ID: 48780
Agnostic Explanation of Model Change based on Feature Importance
M. Muschalik, F. Fumagalli, B. Hammer, E. Huellermeier, KI - Künstliche Intelligenz 36 (2022) 211–224.
LibreCat | DOI
 

2021 | Journal Article | LibreCat-ID: 24143
Automated Detection of Side Channels in Cryptographic Protocols: DROWN the ROBOTs!
J.P. Drees, P. Gupta, E. Hüllermeier, T. Jager, A. Konze, C. Priesterjahn, A. Ramaswamy, J. Somorovsky, 14th ACM Workshop on Artificial Intelligence and Security (2021).
LibreCat
 

2021 | Journal Article | LibreCat-ID: 24148
Deep Q-Learning: Theoretical Insights from an Asymptotic Analysis
A. Ramaswamy, E. Hüllermeier, IEEE Transactions on Artificial Intelligence (to Appear) (2021).
LibreCat
 

2021 | Journal Article | LibreCat-ID: 21004
AutoML for Multi-Label Classification: Overview and Empirical Evaluation
M.D. Wever, A. Tornede, F. Mohr, E. Hüllermeier, IEEE Transactions on Pattern Analysis and Machine Intelligence (2021) 1–1.
LibreCat | DOI
 

2021 | Journal Article | LibreCat-ID: 21092
Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning
F. Mohr, M.D. Wever, A. Tornede, E. Hüllermeier, IEEE Transactions on Pattern Analysis and Machine Intelligence (n.d.).
LibreCat
 

2021 | Conference Paper | LibreCat-ID: 21570
Coevolution of Remaining Useful Lifetime Estimation Pipelines for Automated Predictive Maintenance
T. Tornede, A. Tornede, M.D. Wever, E. Hüllermeier, in: Proceedings of the Genetic and Evolutionary Computation Conference, 2021.
LibreCat
 

2021 | Journal Article | LibreCat-ID: 21636
Instance weighting through data imprecisiation
J. Lienen, E. Hüllermeier, International Journal of Approximate Reasoning (2021).
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2021 | Conference Paper | LibreCat-ID: 21637 | OA
From Label Smoothing to Label Relaxation
J. Lienen, E. Hüllermeier, in: Proceedings of the 35th AAAI Conference on Artificial Intelligence, AAAI, AAAI Press, 2021, pp. 8583–8591.
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2021 | Conference Paper | LibreCat-ID: 23779
A Meta-Review on Artificial Intelligence in Product Creation
R. Bernijazov, A. Dicks, R. Dumitrescu, M. Foullois, J.M. Hanselle, E. Hüllermeier, G. Karakaya, P. Ködding, V. Lohweg, M. Malatyali, F. Meyer auf der Heide, M. Panzner, C. Soltenborn, in: Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-21), 2021.
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2021 | Conference Paper | LibreCat-ID: 22280
Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce Model
J. Lienen, E. Hüllermeier, R. Ewerth, N. Nommensen, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2021, pp. 14595–14604.
LibreCat
 

2021 | Preprint | LibreCat-ID: 22509 | OA
Credal Self-Supervised Learning
J. Lienen, E. Hüllermeier, ArXiv:2106.11853 (2021).
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2021 | Conference Paper | LibreCat-ID: 22913
Automated Machine Learning, Bounded Rationality, and Rational Metareasoning
E. Hüllermeier, F. Mohr, A. Tornede, M.D. Wever, in: 2021.
LibreCat
 

2021 | Conference Paper | LibreCat-ID: 27381
Ranking Structured Objects with Graph Neural Networks
C. Damke, E. Hüllermeier, in: C. Soares, L. Torgo (Eds.), Proceedings of The 24th International Conference on Discovery Science (DS 2021), Springer, 2021, pp. 166–180.
LibreCat | DOI | arXiv
 

2021 | Preprint | LibreCat-ID: 30866
Towards Green Automated Machine Learning: Status Quo and Future Directions
T. Tornede, A. Tornede, J.M. Hanselle, M.D. Wever, F. Mohr, E. Hüllermeier, ArXiv:2111.05850 (2021).
LibreCat | arXiv
 

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