Anzahl der Publikationen: 5
Zeitschriftenartikel
Miklautz, Lukas; Mautz, Dominik; Altinigneli, Muzaffer Can; Boehm, Christian und Plant, Claudia
(2020):
Deep Embedded Non-Redundant Clustering.
In: Thirty-Fourth Aaai Conference on Artificial Intelligence, the Thirty-Second Innovative Applications of Artificial Intelligence Conference and the Tenth Aaai Symposium on Educational Advances in Artificial Intelligence, Bd. 34: S. 5174-5181
Konferenzbeitrag
Leiber, Collin ORCID: https://orcid.org/0000-0001-5368-5697; Miklautz, Lukas; Plant, Claudia ORCID: https://orcid.org/0000-0001-5274-8123 und Böhm, Christian ORCID: https://orcid.org/0000-0003-3807-7831
(2023):
Benchmarking Deep Clustering Algorithms With ClustPy.
2023 IEEE International Conference on Data Mining Workshops (ICDMW), Shanghai, China, 01-04 December 2023.
Wang, Jihe; He, Yi; Dinh, Thang N.; Gran, Christan; Qiu, Meikang und Pedrycz, Witold (Hrsg.):
In: 2023 IEEE International Conference on Data Mining Workshops (ICDMW),
Piscataway, NJ: IEEE. S. 625-632
Leiber, Collin ORCID: https://orcid.org/0000-0001-5368-5697; Miklautz, Lukas ORCID: https://orcid.org/0000-0002-2585-5895; Plant, Claudia ORCID: https://orcid.org/0000-0001-5274-8123 und Böhm, Christian ORCID: https://orcid.org/0000-0002-2237-9969
(2023):
Application of Deep Clustering Algorithms.
CIKM '23: The 32nd ACM International Conference on Information and Knowledge Management, Birmingham, United Kingdom, October 21 - 25, 2023.
ACM International Conference on Information and Knowledge Management (Hrsg.),
In: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management,
New York, NY, United States: Association for Computing Machinery. S. 5208-5211
[PDF, 1MB]
Miklautz, Lukas; Teuffenbach, Martin; Weber, Pascal; Perjuci, Rona; Durani, Walid; Böhm, Christian und Plant, Claudia
(2022):
Deep Clustering With Consensus Representations.
22nd IEEE International Conference on Data Mining (ICDM), Orlando, Florida, USA, November 28 - December 1, 2022.
In: 2022 IEEE International Conference on Data Mining (ICDM),
IEEE. S. 1119-1124
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