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2010 – 2019
- 2015
[b1]Ines Färber:
Alternative clustering in subspace projections. RWTH Aachen University, Germany, Apprimus Verlag 2015, ISBN 978-3-86359-368-1- [c16]Michael Hund, Michael Behrisch
, Ines Färber, Michael Sedlmair, Tobias Schreck, Thomas Seidl, Daniel A. Keim:
Subspace Nearest Neighbor Search - Problem Statement, Approaches, and Discussion - Position Paper. SISAP 2015: 307-313 - 2014
- [j3]Stephan Günnemann, Ines Färber, Brigitte Boden, Thomas Seidl:
GAMer: a synthesis of subspace clustering and dense subgraph mining. Knowl. Inf. Syst. 40(2): 243-278 (2014) - [c15]Stephan Günnemann, Ines Färber, Matthias Sebastian Rüdiger, Thomas Seidl:
SMVC: semi-supervised multi-view clustering in subspace projections. KDD 2014: 253-262 - [p1]Ines Färber, Sergej Fries, Götz Marczinski, Thomas Seidl, Nils-Per Steinmann:
Machining Intelligence Network: Data Mining and Semantic Search in Manufacturing Industry. Towards the Internet of Services 2014: 417-424 - 2013
- [c14]Stephan Günnemann, Ines Färber, Sebastian Raubach, Thomas Seidl:
Spectral Subspace Clustering for Graphs with Feature Vectors. ICDM 2013: 231-240 - [c13]Stephan Günnemann, Brigitte Boden, Ines Färber, Thomas Seidl:
Efficient Mining of Combined Subspace and Subgraph Clusters in Graphs with Feature Vectors. PAKDD (1) 2013: 261-275 - 2012
- [c12]Emmanuel Müller, Stephan Günnemann, Ines Färber, Thomas Seidl:
Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data. ICDE 2012: 1207-1210 - [c11]Andrada Tatu, Fabian Maass, Ines Färber, Enrico Bertini, Tobias Schreck, Thomas Seidl, Daniel A. Keim:
Subspace search and visualization to make sense of alternative clusterings in high-dimensional data. IEEE VAST 2012: 63-72 - [c10]Stephan Günnemann, Ines Färber, Thomas Seidl:
Multi-view clustering using mixture models in subspace projections. KDD 2012: 132-140 - [c9]Stephan Günnemann, Ines Färber, Kittipat Virochsiri, Thomas Seidl:
Subspace correlation clustering: finding locally correlated dimensions in subspace projections of the data. KDD 2012: 352-360 - 2011
- [j2]Christoph Busch, Ulrike Korte, Sebastian Abt, Christian Böhm, Ines Färber, Sergej Fries, Johannes Merkle, Claudia Nickel, Alexander Nouak, Alexander Opel, Annahita Oswald, Thomas Seidl, Bianca Wackersreuther, Peter Wackersreuther, Xuebing Zhou:
Biometric Template Protection - Ein Bericht über das Projekt BioKeyS. Datenschutz und Datensicherheit 35(3): 183-191 (2011) - [c8]Christian Böhm, Ines Färber, Sergej Fries, Ulrike Korte, Johannes Merkle, Annahita Oswald, Thomas Seidl, Bianca Wackersreuther, Peter Wackersreuther:
Efficient Database Techniques for Identification with Fuzzy Vault Templates. BIOSIG 2011: 115-126 - [c7]Christian Böhm, Ines Färber, Sergej Fries, Ulrike Korte, Johannes Merkle, Annahita Oswald, Thomas Seidl, Bianca Wackersreuther, Peter Wackersreuther:
Filtertechniken für geschützte biometrische Datenbanken. BTW 2011: 379-389 - [c6]Stephan Günnemann, Ines Färber, Emmanuel Müller, Ira Assent, Thomas Seidl:
External evaluation measures for subspace clustering. CIKM 2011: 1363-1372 - 2010
- [j1]Stephan Günnemann, Ines Färber, Hardy Kremer, Thomas Seidl:
CoDA: Interactive Cluster Based Concept Discovery. Proc. VLDB Endow. 3(2): 1633-1636 (2010) - [c5]Stephan Günnemann, Ines Färber, Brigitte Boden, Thomas Seidl:
Subspace Clustering Meets Dense Subgraph Mining: A Synthesis of Two Paradigms. ICDM 2010: 845-850 - [c4]Emmanuel Müller, Stephan Günnemann, Ines Färber, Thomas Seidl:
Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data. ICDM 2010: 1220 - [c3]Stephan Günnemann, Hardy Kremer, Ines Färber, Thomas Seidl:
MCExplorer: Interactive Exploration of Multiple (Subspace) Clustering Solutions. ICDM Workshops 2010: 1387-1390
2000 – 2009
- 2009
- [c2]Stephan Günnemann, Emmanuel Müller, Ines Färber, Thomas Seidl:
Detection of orthogonal concepts in subspaces of high dimensional data. CIKM 2009: 1317-1326 - [c1]Ines Färber:
Mining orthogonaler Konzepte in hochdimensionalen Datenbanken. Informatiktage 2009: 153-156
Coauthor Index
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