Publications

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Maaß F.  2013.  An approach for steerable visual subspace search for pattern discovery in high dimensional data. Universität Konstanz. Master of Science
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Tatu A, Zhang L, Bertini E, Schreck T, Keim DA, Bremm S, von Landesberger T.  2012.  ClustNails: Visual Analysis of Subspace Clusters. Tsinghua Science and Technology, Special Issue on Visualization and Computer Graphics. 17(4):419-428.
Gerwert P.  2013.  Constraint-based Susbpace Clustering utilizing Combined Graph clustering Methods. RWTH Aachen. Master of Science
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Boden B, Haag R, Seidl T.  2013.  Detecting and Exploring Clusters in Attributed Graphs. Proceedings of the 22nd ACM Conference on Information and Knowledge Management (CIKM 2013).
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Rüdiger M.  2013.  Integration von Vorwissen in mischverteilungsbasierte Multi-View Subspace Clusteringverfahren. RWTH Aachen. Master of Science
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Stepien G.  2013.  Modularity-based determination of node clusters and their significant edge subspaces in networks with vector-labeled edges. RWTH Aachen. Bachelor of Science
Günnemann S, Färber I, Seidl T.  2012.  Multi-view clustering using mixture models in subspace projections. Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'12). :132-140.
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Raubach S.  2012.  Projected Spectral Clustering on Graphs with Feature Vectors. RWTH Aachen. Master of Science
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Günnemann S, Färber I, Mausbach T, Seidl T.  2014.  SMVC: Semi-Supervised Multi-View Clustering in Subspace Projections. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'14). 20:253-262.
Günnemann S, Färber I, Raubach S, Seidl T.  2013.  Spectral Subspace Clustering for Graphs with Feature Vectors. Proceedings of the IEEE International Conference on Data Mining (ICDM 2013).
Günnemann S, Färber I, Virochsiri K, Seidl T.  2012.  Subspace correlation clustering: finding locally correlated dimensions in subspace projections of the data. Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'12). :352-360.
Tatu A, Maaß F, Färber I, Bertini E, Schreck T, Seidl T, Keim DA.  2012.  Subspace Search and Visualization to Make Sense of Alternative Clusterings in High-Dimensional Data. Procedings of IEEE Symposium on Visual Analytics Science and Technology (VAST). :63-72.
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Sedlmair M, Tatu A, Munzner T, Tory M.  2012.  A Taxonomy of Visual Cluster Separation Factors. Computer Graphics Forum (Proc. EuroVis 2012). 31(3):1335-1344.
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Tatu A.  2013.  Visual Analytics of Patterns in High-Dimensional Data. Universität Konstanz. Dr.