Anzahl der Publikationen: 18
Zeitschriftenartikel
Stock, Michiel; Fober, Thomas; Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108; Glinca, Serghei; Klebe, Gerhard; Pahikkala, Tapio; Airola, Antti; De Baets, Bernard und Waegeman, Willem
(2014):
Identification of Functionally Related Enzymes by Learning-to-Rank Methods.
In: IEEE/ACM Transactions on Computational Biology and Bioinformatics, Bd. 11, Nr. 6: S. 1157-1169
Buchbeitrag
Dembczyński, Krzysztof; Kotłowski, Wojciech; Waegeman, Willem; Busa-Fekete, Róbert und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(2016):
Consistency of Probabilistic Classifier Trees.
In: Frasconi, Paolo; Landwehr, Niels; Manco, Giuseppe und Vreeken, Jilles (Hrsg.):
Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part II. Lecture Notes in Computer Science, Bd. 9852. Cham: Springer. S. 511-526
[PDF, 322kB]
Dembczyński, Krzysztof; Waegeman, Willem und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(August 2012):
An Analysis of Chaining in Multi-Label Classification.
In: De Raedt, Luc; Bessiere, Christian; Dubois, Didier; Doherty, Patrick; Frasconi, Paolo; Heintz, Fredrik und Lucas, Peter (Hrsg.):
ECAI 2012 : 20th European Conference on Artificial Intelligence, 27 - 31 August 2012, Montpellier, France. Frontiers in Artificial Intelligence and Applications, Bd. 242. Amsterdam: IOS Press. S. 294-299
[PDF, 258kB]
Dembczyński, Krzysztof; Waegeman, Willem; Cheng, Weiwei und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(2010):
Regret Analysis for Performance Metrics in Multi-Label Classification: The Case of Hamming and Subset Zero-One Loss.
In: Balcázar, José Luis; Bonchi, Francesco; Gionis, Aristides und Sebag, Michèle (Hrsg.):
Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010, Proceedings, Part I. Lecture Notes in Computer Science, Bd. 6321. Berlin, Heidelberg: Springer. S. 280-295
Konferenzbeitrag
Juergens, Mira; Meinert, Nis; Bengs, Viktor ORCID: https://orcid.org/0000-0001-6988-6186; Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108 und Waegeman, Willem
(Juli 2024):
Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods?
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. 22624-22642
[PDF, 8MB]
Mortier, Thomas ORCID: https://orcid.org/0000-0001-9650-9263; Bengs, Viktor ORCID: https://orcid.org/0000-0001-6988-6186; Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108; Luca, Stijn und Waegeman, Willem ORCID: https://orcid.org/0000-0002-5950-3003
(April 2023):
On the Calibration of Probabilistic Classifier Sets.
26th International Conference on Artificial Intelligence and Statistics (AISTATS 2023), Valencia, Spain, 25-27 April, 2023.
Ruiz, Francisco; Dy, Jennifer und van de Meent, Jan-Willem (Hrsg.):
In: Proceedings of The 26th International Conference on Artificial Intelligence and Statistics,
Bd. 206
PMLR. S. 8857-8870
[PDF, 764kB]
Bengs, Viktor ORCID: https://orcid.org/0000-0001-6988-6186; Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108 und Waegeman, Willem ORCID: https://orcid.org/0000-0002-5950-3003
(2023):
On Second-Order Scoring Rules for Epistemic Uncertainty Quantification.
40th International Conference on Machine Learning (ICML 2023), Hawaii, USA, 23-29 July, 2023.
Krause, Andreas; Brunskill, Emma; Cho, Kyunghyun; Engelhardt, Barbara; Sabato, Sivan und Scarlett, Jonathan (Hrsg.):
In: Proceedings of the 40th International Conference on Machine Learning,
Bd. 202
PMLR. S. 2078-2091
[PDF, 400kB]
Mortier, Thomas ORCID: https://orcid.org/0000-0001-9650-9263; Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108; Dembczyński, Krzysztof und Waegeman, Willem ORCID: https://orcid.org/0000-0002-5950-3003
(August 2022):
Set-valued prediction in hierarchical classification with constrained representation complexity.
38th Conference on Uncertainty in Artificial Intelligence, Eindhoven, Netherlands, 1-5 August 2022.
Cussens, James und Zhang, Kun (Hrsg.):
In: Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence,
Bd. 180
PMLR. S. 1392-1401
[PDF, 600kB]
Dembczyński, Krzysztof; Jachnik, Arkadiusz; Kotlowski, Wojciech; Waegeman, Willem und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(2013):
Optimizing the F-Measure in Multi-Label Classification: Plug-in Rule Approach versus Structured Loss Minimization.
ICML'13: 30th International Conference on International Conference on Machine Learning, Atlanta GA USA, June 16 - 21, 2013.
Dasgupta, Sanjoy und McAllester, David (Hrsg.):
In: Proceedings of the 30th International Conference on Machine Learning,
Bd. 28, Nr. 3
S. 1030-1038
[PDF, 378kB]
Cheng, Weiwei; Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108; Waegeman, Willem und Welker, Volkmar
(2012):
Label Ranking with Partial Abstention based on Thresholded Probabilistic Models.
25. NIPS 2012, Lake Tahoe, Nevada, USA, December 3-8, 2012.
Advances in Neural Information Processing Systems.
Bd. 25
S. 2510-2518
[PDF, 252kB]
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Sat Dec 21 21:16:41 2024 CET
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