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Maurice Funk
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Year
Learning description logic concepts: When can positive and negative examples be separated
M Funk, JC Jung, C Lutz, H Pulcini, F Wolter
Proceedings of IJCAI 19, 2019
452019
Actively learning concepts and conjunctive queries under ELr-ontologies
M Funk, JC Jung, C Lutz
arXiv preprint arXiv:2105.08326, 2021
142021
Frontiers and Exact Learning of ELI Queries under DL-Lite Ontologies
M Funk, JC Jung, C Lutz
arXiv preprint arXiv:2204.14172, 2022
132022
Extremal fitting problems for conjunctive queries
B Ten Cate, V Dalmau, M Funk, C Lutz
Proceedings of the 42nd ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of …, 2023
122023
SAT-based PAC learning of description logic concepts
B Ten Cate, M Funk, JC Jung, C Lutz
Proc. of IJCAI, 2023
82023
Concept-by-example in EL knowledge bases
M Funk
Master's thesis, University of Bremen, 2019
72019
On the non-efficient PAC learnability of conjunctive queries
B ten Cate, M Funk, JC Jung, C Lutz
Information Processing Letters, 106431, 2023
6*2023
Actively Learning ELI Queries under DL-Lite Ontologies.
M Funk, JC Jung, C Lutz
Description Logics, 2021
42021
Towards Ontology Construction with Language Models
M Funk, S Hosemann, JC Jung, C Lutz
arXiv preprint arXiv:2309.09898, 2023
32023
Exact Learning of ELI Queries in the Presence of DL-Lite-Horn Ontologies.
M Funk, JC Jung, C Lutz
Description Logics, 2022
32022
Fitting Algorithms for Conjunctive Queries
B ten Cate, M Funk, J Christoph Jung, C Lutz
ACM SIGMOD Record 52 (4), 6-18, 2024
12024
Extremal Fitting CQs do not Generalize
B Cate, M Funk, JC Jung, C Lutz
arXiv preprint arXiv:2312.03407, 2023
1*2023
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