• 2024
  • inbook
C. Balestra, A. Ferrara and E. MüllerFairMC Fair—Markov Chain Rank Aggregation Methods in Lecture Notes in Computer Science, Springer Nature Switzerland, 2024, pp. 315—321.
[DOI]
  • inbook
S. Klüttermann, C. Balestra and E. MüllerOn the Efficient Explanation of Outlier Detection Ensembles Through Shapley Values in Advances in Knowledge Discovery and Data Mining, Springer Nature Singapore, 2024, pp. 43—55.
[DOI]
  • inbook
N. R. Nair, L. Schmid, C. Reining, F. Moya Rueda, M. Pauly and G. A. Fink Representation Biases in Time-Series Human Activity Recognition with Small Sample Sizes in Pattern Recognition, Springer Nature Switzerland, Dec. 2024, pp. 33—48.
[DOI]
  • 2023
  • inbook
S. Klüttermann, J. Rutinowski, A. Nguyen, C. Reining, M. Roidl and E. MüllerOn Graph Representation based Re-Identification — A Proof of Concept in 2023 IEEE International Conference on Data Mining Workshops (ICDMW), IEEE, Dec. 2023.
[DOI]
  • inbook
G. Schmitz, D. Wilmes, A. Gerharz, D. Horn and E. MüllerContextual Shift Method (CSM) in Lecture Notes in Computer Science, Springer Nature Switzerland, 2023, pp. 101—106.
[DOI]
  • inbook
M. Wischnewski and A. Wermter Is Foreign Language News More or Less Credible Than Native Language News? Examining the Foreign Language Effect on Credibility Perceptions in Disinformation in Open Online Media, Springer Nature Switzerland, 2023, pp. 175—189.
[DOI]
  • inbook
L. Kuhlmann, D. Wilmes, E. Müller, M. Pauly and D. Horn RODD: Robust Outlier Detection in Data Cubes in Lecture Notes in Computer Science, Springer Nature Switzerland, 2023, pp. 325—339.
[DOI]
  • inbook
A. Baudzus, B. Li, A. Jadid and E. MüllerThe Good, The Bad, and The Average: Benchmarking of Reconstruction Based Multivariate Time Series Anomaly Detection in Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track, Springer Nature Switzerland, 2023, pp. 356—360.
[DOI]
  • 2022
  • inbook
C. Newen and E. MüllerUnsupervised DeepView: Global Explainability of Uncertainties for High Dimensional Data in 2022 IEEE International Conference on Knowledge Graph (ICKG), IEEE, Nov. 2022, pp. 196—202.
[DOI]
  • inbook
C. Newen and E. MüllerUnsupervised DeepView: Global Uncertainty Visualization for High Dimensional Data in 2022 IEEE International Conference on Data Mining Workshops (ICDMW), IEEE, Nov. 2022, pp. 1—8.
[DOI]
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