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Springe zu: Konferenzbeitrag
Anzahl der Publikationen: 7
Konferenzbeitrag
Fumagalli, Fabian; Muschalik, Maximilian 
ORCID: https://orcid.org/0000-0002-6921-0204; Kolpaczki, Patrick; HÜllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108 und Hammer, Barbara ORCID: https://orcid.org/0000-0002-0935-5591
(Juli 2024):
KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions.
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. 14308-14342
[PDF, 1MB]
ORCID: https://orcid.org/0000-0002-6921-0204; Kolpaczki, Patrick; HÜllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108 und Hammer, Barbara ORCID: https://orcid.org/0000-0002-0935-5591
(Juli 2024):
KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions.
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. 14308-14342
[PDF, 1MB]
Kolpaczki, Patrick; Haselbeck, Georg und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(Juli 2024):
How Much Can Stratification Improve the Approximation of Shapley Values?
Explainable Artificial Intelligence, Valletta, Malta, 17. –19. July 2024.
Longo, Luca; Lapuschkin, Sebastian und Seifert, Christin (Hrsg.):
In: Communications in Computer and Information Science,
Bd. 2154
Springer, Cham. S. 489-512
ORCID: https://orcid.org/0000-0002-9944-4108
(Juli 2024):
How Much Can Stratification Improve the Approximation of Shapley Values?
Explainable Artificial Intelligence, Valletta, Malta, 17. –19. July 2024.
Longo, Luca; Lapuschkin, Sebastian und Seifert, Christin (Hrsg.):
In: Communications in Computer and Information Science,
Bd. 2154
Springer, Cham. S. 489-512
Kolpaczki, Patrick; Muschalik, Maximilian ORCID: https://orcid.org/0000-0002-6921-0204; Fumagalli, Fabian ORCID: https://orcid.org/0000-0003-3955-3510; Hammer, Barbara ORCID: https://orcid.org/0000-0002-0935-5591 und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(Mai 2024):
SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification.
27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), Valencia, Spain, 2. - 4. May 2024.
In: Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, Proceedings of Machine Learning Research
Bd. 238
PMLR. S. 3520-3528
[PDF, 8MB]
ORCID: https://orcid.org/0000-0002-6921-0204; Fumagalli, Fabian ORCID: https://orcid.org/0000-0003-3955-3510; Hammer, Barbara ORCID: https://orcid.org/0000-0002-0935-5591 und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(Mai 2024):
SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification.
27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), Valencia, Spain, 2. - 4. May 2024.
In: Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, Proceedings of Machine Learning Research
Bd. 238
PMLR. S. 3520-3528
[PDF, 8MB]
Kolpaczki, Patrick; Bengs, Viktor ORCID: https://orcid.org/0000-0001-6988-6186; Muschalik, Maximilian ORCID: https://orcid.org/0000-0002-6921-0204 und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(2024):
Approximating the Shapley Value without Marginal Contributions.
AAAI Conference on Artificial Intelligence 2024, Vancouver, Canada, 20-27 February 2024.
Proceedings of the AAAI Conference on Artificial Intelligence.
Bd. 38, Nr. 12
S. 13246-13255
[PDF, 2MB]
ORCID: https://orcid.org/0000-0001-6988-6186; Muschalik, Maximilian ORCID: https://orcid.org/0000-0002-6921-0204 und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(2024):
Approximating the Shapley Value without Marginal Contributions.
AAAI Conference on Artificial Intelligence 2024, Vancouver, Canada, 20-27 February 2024.
Proceedings of the AAAI Conference on Artificial Intelligence.
Bd. 38, Nr. 12
S. 13246-13255
[PDF, 2MB]
Muschalik, Maximilian ORCID: https://orcid.org/0000-0002-6921-0204; Baniecki, Hubert; Fumagalli, Fabian ORCID: https://orcid.org/0000-0003-3955-3510; Kolpaczki, Patrick; Hammer, Barbara ORCID: https://orcid.org/0000-0002-0935-5591 und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(2024):
shapiq: Shapley Interactions for Machine Learning.
The Thirty-eight Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, BC, Canada, 10. - 15. December 2024.
[PDF, 4MB]
ORCID: https://orcid.org/0000-0002-6921-0204; Baniecki, Hubert; Fumagalli, Fabian ORCID: https://orcid.org/0000-0003-3955-3510; Kolpaczki, Patrick; Hammer, Barbara ORCID: https://orcid.org/0000-0002-0935-5591 und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(2024):
shapiq: Shapley Interactions for Machine Learning.
The Thirty-eight Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, BC, Canada, 10. - 15. December 2024.
[PDF, 4MB]
Fumagalli, Fabian ORCID: https://orcid.org/0000-0003-3955-3510; Muschalik, Maximilian ORCID: https://orcid.org/0000-0002-6921-0204; Kolpaczki, Patrick; Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108 und Hammer, Barbara ORCID: https://orcid.org/0000-0002-0935-5591
(Dezember 2023):
SHAP-IQ: Unified Approximation of any-order Shapley Interactions.
37th Annual Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, Louisiana, USA, 10. - 16. December 2023.
In: Proceedings of the 37th Annual Conference on Neural Information Processing Systems, Advances in Neural Information Processing Systems
Bd. 36
Curran Associates, Inc.. S. 11515-11551
[PDF, 1MB]
ORCID: https://orcid.org/0000-0003-3955-3510; Muschalik, Maximilian ORCID: https://orcid.org/0000-0002-6921-0204; Kolpaczki, Patrick; Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108 und Hammer, Barbara ORCID: https://orcid.org/0000-0002-0935-5591
(Dezember 2023):
SHAP-IQ: Unified Approximation of any-order Shapley Interactions.
37th Annual Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, Louisiana, USA, 10. - 16. December 2023.
In: Proceedings of the 37th Annual Conference on Neural Information Processing Systems, Advances in Neural Information Processing Systems
Bd. 36
Curran Associates, Inc.. S. 11515-11551
[PDF, 1MB]
Kolpaczki, Patrick; Bengs, Viktor und Hüllermeier, Eyke ORCID: https://orcid.org/0000-0002-9944-4108
(September 2021):
Identifying Top-k Players in Cooperative Games via Shapley Bandits.
LWDA’21: Lernen, Wissen, Daten, Analysen, Munich, Germany, 1. - 3. September, 2021.
In: Proceedings of the LWDA 2021 Workshops: FGWM, KDML, FGWI-BIA, and FGIR,
Bd. 2993
S. 133-144
[PDF, 805kB]
ORCID: https://orcid.org/0000-0002-9944-4108
(September 2021):
Identifying Top-k Players in Cooperative Games via Shapley Bandits.
LWDA’21: Lernen, Wissen, Daten, Analysen, Munich, Germany, 1. - 3. September, 2021.
In: Proceedings of the LWDA 2021 Workshops: FGWM, KDML, FGWI-BIA, and FGIR,
Bd. 2993
S. 133-144
[PDF, 805kB]