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Konferenzbeitrag
Gilhuber, Sandra; Hvingelby, Rasmus; Fok, Mang Ling Ada und Seidl, Thomas 
ORCID: https://orcid.org/0000-0002-4861-1412
(2023):
How to Overcome Confirmation Bias in Semi-Supervised Image Classification by Active Learning.
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Turin, Italy, 18.-22. September 2023.
Koutra, Danai; Plant, Claudia; Gomez Rodriguez, Manuel; Baralis, Elena und Bonchi, Francesco (Hrsg.):
In: Machine Learning and Knowledge Discovery in Databases: Research Track, Lecture Notes in Artificial Intelligence
Bd. 14170
Cham: Springer. S. 330-347
ORCID: https://orcid.org/0000-0002-4861-1412
(2023):
How to Overcome Confirmation Bias in Semi-Supervised Image Classification by Active Learning.
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Turin, Italy, 18.-22. September 2023.
Koutra, Danai; Plant, Claudia; Gomez Rodriguez, Manuel; Baralis, Elena und Bonchi, Francesco (Hrsg.):
In: Machine Learning and Knowledge Discovery in Databases: Research Track, Lecture Notes in Artificial Intelligence
Bd. 14170
Cham: Springer. S. 330-347
Goschenhofer, Jann; Hvingelby, Rasmus; Rügamer, David ORCID: https://orcid.org/0000-0002-8772-9202; Thomas, Janek; Wagner, Moritz und Bischl, Bernd
(2021):
Deep Semi-supervised Learning for Time Series Classification.
2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA), Pasadena, CA, USA, 13-16 December 2021.
In: 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA),
New York: IEEE. S. 422-428
ORCID: https://orcid.org/0000-0002-8772-9202; Thomas, Janek; Wagner, Moritz und Bischl, Bernd
(2021):
Deep Semi-supervised Learning for Time Series Classification.
2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA), Pasadena, CA, USA, 13-16 December 2021.
In: 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA),
New York: IEEE. S. 422-428