From Label Smoothing to Label Relaxation J Lienen, E Hüllermeier Proceedings of the 35th AAAI Conference on Artificial Intelligence, AAAI …, 2021 | 52 | 2021 |
Credal Self-Supervised Learning J Lienen, E Hüllermeier Advances in Neural Information Processing Systems 34, 2021 | 24 | 2021 |
Monocular Depth Estimation via Listwise Ranking Using the Plackett-Luce Model J Lienen, E Hüllermeier, R Ewerth, N Nommensen Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 15 | 2021 |
Memorization-Dilation: Modeling Neural Collapse Under Noise DA Nguyen*, R Levie*, J Lienen*, G Kutyniok, E Hüllermeier International Conference on Learning Representations, ICLR, 2023 | 11* | 2023 |
Instance weighting through data imprecisiation J Lienen, E Hüllermeier International Journal of Approximate Reasoning 134, 1-14, 2021 | 11 | 2021 |
Conformal Credal Self-Supervised Learning J Lienen, C Demir, E Hüllermeier Conformal and Probabilistic Prediction with Applications, 214-233, 2023 | 7 | 2023 |
Kronecker Decomposition for Knowledge Graph Embeddings C Demir, J Lienen, AC Ngonga Ngomo Proceedings of the 33rd ACM Conference on Hypertext and Social Media, 1-10, 2022 | 5 | 2022 |
Robust Regression for Monocular Depth Estimation J Lienen, N Nommensen, R Ewerth, E Hüllermeier Asian Conference on Machine Learning, 1001-1016, 2021 | 3 | 2021 |
Mitigating Label Noise through Data Ambiguation J Lienen, E Hüllermeier Proceedings of the AAAI Conference on Artificial Intelligence 38 (12), 13799 …, 2024 | 2 | 2024 |
Scikit-Weak: A Python Library for Weakly Supervised Machine Learning A Campagner, J Lienen, E Hüllermeier, D Ciucci International Joint Conference on Rough Sets, 57-70, 2022 | 2 | 2022 |
Detecting Novelties with Empty Classes S Uhlemeyer, J Lienen, E Hüllermeier, H Gottschalk arXiv preprint arXiv:2305.00983, 2023 | | 2023 |
Active Automated Machine Learning with Self-Training V Margraf, J Lienen, E Hüllermeier, M Wever | | |