Dominik Mautz

According to our database, Dominik Mautz authored at least 15 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Incorporating User's Preference into Attributed Graph Clustering : Extended abstract.

Wei Ye, Dominik Mautz, Christian Böhm, Ambuj K. Singh, Claudia Plant

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

2022

Exploratory cluster analysis with jointly optimized feature transformations.

Dominik Mautz

PhD thesis, 2022

Automatic Parameter Selection for Non-Redundant Clustering.

Collin Leiber, Dominik Mautz, Claudia Plant, Christian Böhm

Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

DBHD: Density-based clustering for highly varying density.

Walid Durani, Dominik Mautz, Claudia Plant, Christian Böhm

Proceedings of the IEEE International Conference on Data Mining, 2022

2021

Incorporating User's Preference into Attributed Graph Clustering.

Wei Ye, Dominik Mautz, Christian Böhm, Ambuj K. Singh, Claudia Plant

IEEE Trans. Knowl. Data Eng., 2021

Details (Don't) Matter: Isolating Cluster Information in Deep Embedded Spaces.

Lukas Miklautz, Lena G. M. Bauer, Dominik Mautz, Sebastian Tschiatschek, Christian Böhm, Claudia Plant

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

2020

Non-Redundant Subspace Clusterings with Nr-Kmeans and Nr-DipMeans.

Dominik Mautz, Wei Ye, Claudia Plant, Christian Böhm

ACM Trans. Knowl. Discov. Data, 2020

DeepECT: The Deep Embedded Cluster Tree.

Dominik Mautz, Claudia Plant, Christian Böhm

Data Sci. Eng., 2020

Deep Embedded Non-Redundant Clustering.

Lukas Miklautz, Dominik Mautz, Muzaffer Can Altinigneli, Christian Böhm, Claudia Plant

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Deep Embedded Cluster Tree.

Dominik Mautz, Claudia Plant, Christian Böhm

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Anomaly Detection in Time Series using Generative Adversarial Networks.

Fiete Lüer, Dominik Mautz, Christian Böhm

Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

2018

Discovering Non-Redundant K-means Clusterings in Optimal Subspaces.

Dominik Mautz, Wei Ye, Claudia Plant, Christian Böhm

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

2017

Learning from Labeled and Unlabeled Vertices in Networks.

Wei Ye, Linfei Zhou, Dominik Mautz, Claudia Plant, Christian Böhm

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Towards an Optimal Subspace for K-Means.

Dominik Mautz, Wei Ye, Claudia Plant, Christian Böhm

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

2016

Subspace Clustering Ensembles through Tensor Decomposition.

Dominik Mautz, Christian Böhm, Claudia Plant

Proceedings of the IEEE International Conference on Data Mining Workshops, 2016