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Gruppiert nach: Dokumententyp | Veröffentlichungsdatum
Anzahl der Publikationen: 16

Zeitschriftenartikel

Mortier, Thomas ORCID logoORCID: https://orcid.org/0000-0001-9650-9263; Wydmuch, Marek; Dembczyński, Krzysztof; Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 und Waegeman, Willem (Mai 2021): Efficient set-valued prediction in multi-class classification. In: Data Mining and Knowledge Discovery, Bd. 35, Nr. 4: S. 1435-1469

Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 und Waegeman, Willem (März 2021): Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods. In: Machine Learning, Nr. 3: S. 457-506

Mortier, Thomas; Wydmuch, Marek; Dembczynski, Krzysztof; Hüllermeier, Eyke und Waegeman, Willem (2021): Efficient set-valued prediction in multi-class classification. In: Data Mining and Knowledge Discovery, Bd. 35, Nr. 4: S. 1435-1469

Waegeman, Willem ORCID logoORCID: https://orcid.org/0000-0002-5950-3003; Dembczyński, Krzysztof und Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 (2019): Multi-target prediction: a unifying view on problems and methods. In: Data Mining and Knowledge Discovery, Bd. 33, Nr. 2: S. 293-324

Waegeman, Willem ORCID logoORCID: https://orcid.org/0000-0002-5950-3003; Dembczyński, Krzysztof; Jachnik, Arkadiusz; Cheng, Weiwei und Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 (November 2014): On the Bayes-Optimality of F-Measure Maximizers. In: Journal of Machine Learning Research, Bd. 15, 103: S. 3513-3568

Stock, Michiel; Fober, Thomas; Hüllermeier, Eyke ORCID logoORCID: 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

Dembczyński, Krzysztof; Waegeman, Willem; Cheng, Weiwei und Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 (2012): On label dependence and loss minimization in multi-label classification. In: Machine Learning, Bd. 88, Nr. 1-2: S. 5-45

Buchbeitrag

Dembczyński, Krzysztof; Kotłowski, Wojciech; Waegeman, Willem; Busa-Fekete, Róbert und Hüllermeier, Eyke ORCID logoORCID: 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

Dembczyński, Krzysztof; Waegeman, Willem und Hüllermeier, Eyke ORCID logoORCID: 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 logoORCID: 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

Mortier, Thomas ORCID logoORCID: https://orcid.org/0000-0001-9650-9263; Bengs, Viktor ORCID logoORCID: https://orcid.org/0000-0001-6988-6186; Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108; Luca, Stijn und Waegeman, Willem ORCID logoORCID: 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

Bengs, Viktor ORCID logoORCID: https://orcid.org/0000-0001-6988-6186; Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 und Waegeman, Willem ORCID logoORCID: 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

Bengs, Viktor ORCID logoORCID: https://orcid.org/0000-0001-6988-6186; Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108 und Waegeman, Willem ORCID logoORCID: https://orcid.org/0000-0002-5950-3003 (28. November 2022): Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation. Advances in Neural Information Processing Systems, New Orleans, USA, 28 November - 9 December 2022. Oh, Alice H.; Agarwal, Alekh; Belgrave, Danielle und Cho, Kyunghyun (Hrsg.):

Mortier, Thomas ORCID logoORCID: https://orcid.org/0000-0001-9650-9263; Hüllermeier, Eyke ORCID logoORCID: https://orcid.org/0000-0002-9944-4108; Dembczyński, Krzysztof und Waegeman, Willem ORCID logoORCID: 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

Dembczyński, Krzysztof; Jachnik, Arkadiusz; Kotlowski, Wojciech; Waegeman, Willem und Hüllermeier, Eyke ORCID logoORCID: 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

Cheng, Weiwei; Hüllermeier, Eyke ORCID logoORCID: 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

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