Julian Lienen

julian.lienen@uni-paderborn.de
ID
44040

14 Publications

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[14]
2023 | Preprint | LibreCat-ID: 44512 | OA
Detecting Novelties with Empty Classes
S. Uhlemeyer, J. Lienen, E. Hüllermeier, H. Gottschalk, ArXiv:2305.00983 (2023).
LibreCat | Download (ext.) | arXiv
 
[13]
2023 | Conference Paper | LibreCat-ID: 31880 | OA
Memorization-Dilation: Modeling Neural Collapse Under Noise
D.A. Nguyen, R. Levie, J. Lienen, G. Kutyniok, E. Hüllermeier, in: International Conference on Learning Representations, ICLR, 2023.
LibreCat | Download (ext.)
 
[12]
2023 | Preprint | LibreCat-ID: 45911 | OA
Mitigating Label Noise through Data Ambiguation
J. Lienen, E. Hüllermeier, ArXiv:2305.13764 (2023).
LibreCat | Download (ext.) | arXiv
 
[11]
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
 
[10]
2022 | Preprint | LibreCat-ID: 31545 | OA
Kronecker Decomposition for Knowledge Graph Embeddings
C. Demir, J. Lienen, A.-C. Ngonga Ngomo, ArXiv:2205.06560 (2022).
LibreCat | Download (ext.)
 
[9]
2022 | Preprint | LibreCat-ID: 31546 | OA
Conformal Credal Self-Supervised Learning
J. Lienen, C. Demir, E. Hüllermeier, ArXiv:2205.15239 (2022).
LibreCat | Download (ext.)
 
[8]
2021 | Conference Paper | LibreCat-ID: 27161
Credal Self-Supervised Learning
J. Lienen, E. Hüllermeier, in: Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems, NeurIPS, 2021.
LibreCat
 
[7]
2021 | Conference Paper | LibreCat-ID: 27162
Robust Regression for Monocular Depth Estimation
J. Lienen, N. Nommensen, R. Ewerth, E. Hüllermeier, in: 13th Asian Conference on Machine Learning, ACML, 2021.
LibreCat
 
[6]
2021 | Journal Article | LibreCat-ID: 21636
Instance weighting through data imprecisiation
J. Lienen, E. Hüllermeier, International Journal of Approximate Reasoning (2021).
LibreCat | Download (ext.)
 
[5]
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.
LibreCat | Download (ext.)
 
[4]
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
 
[3]
2021 | Preprint | LibreCat-ID: 22509 | OA
Credal Self-Supervised Learning
J. Lienen, E. Hüllermeier, ArXiv:2106.11853 (2021).
LibreCat | Download (ext.)
 
[2]
2020 | Preprint | LibreCat-ID: 20211 | OA
Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce model
J. Lienen, E. Hüllermeier, ArXiv:2010.13118 (2020).
LibreCat | Download (ext.)
 
[1]
2019 | Mastersthesis | LibreCat-ID: 16415
Automated Feature Engineering on Time Series Data
J. Lienen, Automated Feature Engineering on Time Series Data, 2019.
LibreCat
 
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14 Publications

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[14]
2023 | Preprint | LibreCat-ID: 44512 | OA
Detecting Novelties with Empty Classes
S. Uhlemeyer, J. Lienen, E. Hüllermeier, H. Gottschalk, ArXiv:2305.00983 (2023).
LibreCat | Download (ext.) | arXiv
 
[13]
2023 | Conference Paper | LibreCat-ID: 31880 | OA
Memorization-Dilation: Modeling Neural Collapse Under Noise
D.A. Nguyen, R. Levie, J. Lienen, G. Kutyniok, E. Hüllermeier, in: International Conference on Learning Representations, ICLR, 2023.
LibreCat | Download (ext.)
 
[12]
2023 | Preprint | LibreCat-ID: 45911 | OA
Mitigating Label Noise through Data Ambiguation
J. Lienen, E. Hüllermeier, ArXiv:2305.13764 (2023).
LibreCat | Download (ext.) | arXiv
 
[11]
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
 
[10]
2022 | Preprint | LibreCat-ID: 31545 | OA
Kronecker Decomposition for Knowledge Graph Embeddings
C. Demir, J. Lienen, A.-C. Ngonga Ngomo, ArXiv:2205.06560 (2022).
LibreCat | Download (ext.)
 
[9]
2022 | Preprint | LibreCat-ID: 31546 | OA
Conformal Credal Self-Supervised Learning
J. Lienen, C. Demir, E. Hüllermeier, ArXiv:2205.15239 (2022).
LibreCat | Download (ext.)
 
[8]
2021 | Conference Paper | LibreCat-ID: 27161
Credal Self-Supervised Learning
J. Lienen, E. Hüllermeier, in: Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems, NeurIPS, 2021.
LibreCat
 
[7]
2021 | Conference Paper | LibreCat-ID: 27162
Robust Regression for Monocular Depth Estimation
J. Lienen, N. Nommensen, R. Ewerth, E. Hüllermeier, in: 13th Asian Conference on Machine Learning, ACML, 2021.
LibreCat
 
[6]
2021 | Journal Article | LibreCat-ID: 21636
Instance weighting through data imprecisiation
J. Lienen, E. Hüllermeier, International Journal of Approximate Reasoning (2021).
LibreCat | Download (ext.)
 
[5]
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.
LibreCat | Download (ext.)
 
[4]
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
 
[3]
2021 | Preprint | LibreCat-ID: 22509 | OA
Credal Self-Supervised Learning
J. Lienen, E. Hüllermeier, ArXiv:2106.11853 (2021).
LibreCat | Download (ext.)
 
[2]
2020 | Preprint | LibreCat-ID: 20211 | OA
Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce model
J. Lienen, E. Hüllermeier, ArXiv:2010.13118 (2020).
LibreCat | Download (ext.)
 
[1]
2019 | Mastersthesis | LibreCat-ID: 16415
Automated Feature Engineering on Time Series Data
J. Lienen, Automated Feature Engineering on Time Series Data, 2019.
LibreCat
 
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Search

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