![[höher]](/style/images/multi_up.png)
Eine Ebene höherGruppiert nach:
Dokumententyp
| Veröffentlichungsdatum
Springe zu: Hochschulschrift | Konferenzbeitrag
Anzahl der Publikationen: 8
Hochschulschrift
Sale, Yusuf
(4. Mai 2022):
G-Framework in statistics. Nonlinear expectations for decision-making under uncertainty.
Masterarbeit,
Ludwig-Maximilians-Universität München
(Department of Statistics: Technical Reports) [PDF, 2MB]
(Department of Statistics: Technical Reports) [PDF, 2MB]
Sale, Yusuf
(24. Oktober 2019):
Robuste Minimax-Tests und eine Robustifizierung des Bayes-Faktors.
Bachelorarbeit,
Ludwig-Maximilians-Universität München
(Department of Statistics: Technical Reports) [PDF, 865kB]
(Department of Statistics: Technical Reports) [PDF, 865kB]
Konferenzbeitrag
Sale, Yusuf; Hofman, Paul; Löhr, Timo 
ORCID: https://orcid.org/0000-0001-7150-4618; Wimmer, Lisa; Nagler, Thomas und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(15. Juli 2024):
Label-wise Aleatoric and Epistemic Uncertainty Quantification.
Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, Barcelona, Spain, 15. - 19. July 2024.
Kiyavash, Negar und Mooij, Joris M. (Hrsg.):
Proceedings of Machine Learning Research.
Bd. 244
PMLR. S. 3159-3179
[PDF, 1MB]
ORCID: https://orcid.org/0000-0001-7150-4618; Wimmer, Lisa; Nagler, Thomas und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(15. Juli 2024):
Label-wise Aleatoric and Epistemic Uncertainty Quantification.
Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence, Barcelona, Spain, 15. - 19. July 2024.
Kiyavash, Negar und Mooij, Joris M. (Hrsg.):
Proceedings of Machine Learning Research.
Bd. 244
PMLR. S. 3159-3179
[PDF, 1MB]
Sale, Yusuf; Bengs, Viktor ORCID: https://orcid.org/0000-0001-6988-6186; Caprio, Michele und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(Juli 2024):
Second-Order Uncertainty Quantification: A Distance-Based Approach.
41st International Conference on Machine Learning (ICML 2024), Vienna, Austria, 21. - 27. July 2024.
In: Proceedings of the 41st International Conference on Machine Learning, Proceedings of Machine Learning Research
Bd. 235
PMLR. S. 43060-43076
[PDF, 2MB]
ORCID: https://orcid.org/0000-0001-6988-6186; Caprio, Michele und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(Juli 2024):
Second-Order Uncertainty Quantification: A Distance-Based Approach.
41st International Conference on Machine Learning (ICML 2024), Vienna, Austria, 21. - 27. July 2024.
In: Proceedings of the 41st International Conference on Machine Learning, Proceedings of Machine Learning Research
Bd. 235
PMLR. S. 43060-43076
[PDF, 2MB]
Javanmardi, Alireza; Sale, Yusuf; Hofman, Paul und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(September 2023):
Conformal Prediction with Partially Labeled Data.
Twelfth Symposium on Conformal and Probabilistic Prediction with Applications (COPA 2023), Limassol, Cyprus, September 13-15, 2023.
Papadopoulos, Harris; Nguyen, Khuong An; Boström, Henrik und Carlsson, Lars (Hrsg.):
Bd. 204
PMLR. S. 251-266
[PDF, 343kB]
ORCID: https://orcid.org/0000-0002-9944-4108
(September 2023):
Conformal Prediction with Partially Labeled Data.
Twelfth Symposium on Conformal and Probabilistic Prediction with Applications (COPA 2023), Limassol, Cyprus, September 13-15, 2023.
Papadopoulos, Harris; Nguyen, Khuong An; Boström, Henrik und Carlsson, Lars (Hrsg.):
Bd. 204
PMLR. S. 251-266
[PDF, 343kB]
Caprio, Michele; Sale, Yusuf; Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108 und Lee, Insup
(4. August 2023):
A Novel Bayes’ Theorem for Upper Probabilities.
Epi UAI 2023 - First International Workshop on Epistemic Uncertainty in Artificial Intelligence, Pittsburgh, PA, USA, August 4, 2023.
In: Epistemic Uncertainty in Artificial Intelligence,
Bd. 14523
S. 1-12
[PDF, 171kB]
ORCID: https://orcid.org/0000-0002-9944-4108 und Lee, Insup
(4. August 2023):
A Novel Bayes’ Theorem for Upper Probabilities.
Epi UAI 2023 - First International Workshop on Epistemic Uncertainty in Artificial Intelligence, Pittsburgh, PA, USA, August 4, 2023.
In: Epistemic Uncertainty in Artificial Intelligence,
Bd. 14523
S. 1-12
[PDF, 171kB]
Sale, Yusuf; Caprio, Michele und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(August 2023):
Is the volume of a credal set a good measure for epistemic uncertainty?
Thirty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI 2023), Pittsburgh, PA, USA, 1-3 August, 2023.
Evans, Robin J. und Shpitser, Ilya (Hrsg.):
In: Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence,
Bd. 216
PMLR. S. 1795-1804
[PDF, 1MB]
ORCID: https://orcid.org/0000-0002-9944-4108
(August 2023):
Is the volume of a credal set a good measure for epistemic uncertainty?
Thirty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI 2023), Pittsburgh, PA, USA, 1-3 August, 2023.
Evans, Robin J. und Shpitser, Ilya (Hrsg.):
In: Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence,
Bd. 216
PMLR. S. 1795-1804
[PDF, 1MB]
Wimmer, Lisa; Sale, Yusuf; Hofman, Paul; Bischl, Bernd ORCID: https://orcid.org/0000-0001-6002-6980 und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(2023):
Quantifying aleatoric and epistemic uncertainty in machine learning: Are conditional entropy and mutual information appropriate measures?
Thirty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI 2023), Pittsburgh, PA, USA, 1-3 August, 2023.
Evans, Robin J. und Shpitser, Ilya (Hrsg.):
In: Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence,
Bd. 216
PMLR. S. 2282-2292
[PDF, 1MB]
ORCID: https://orcid.org/0000-0001-6002-6980 und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(2023):
Quantifying aleatoric and epistemic uncertainty in machine learning: Are conditional entropy and mutual information appropriate measures?
Thirty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI 2023), Pittsburgh, PA, USA, 1-3 August, 2023.
Evans, Robin J. und Shpitser, Ilya (Hrsg.):
In: Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence,
Bd. 216
PMLR. S. 2282-2292
[PDF, 1MB]