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Research
Research Interests
Research interests are knowledge discovery in databases, machine learning, and
bioinformatics, especially structural bioinformatics and protein classification.
Projects in these areas are permanently available for interested students of
computer science, media informatics, and bioinformatics.
Professional Services
Invited Talks
| [27] | On the Evaluation of Unsupervised Outlier Detection.
Technical University of Vienna, Austria, 18.05.2016.
[ slides (pdf) ] |
| [26] | Get Better Results Faster on Bigger Data: How Approximations can Improve Data Analysis Results.
University of Luxembourg, 19.04.2016.
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| [25] | Outlier Detection with Approximations and Ensembles.
Aarhus University, Denmark, 14.04.2016.
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| [24] | Outlier Detection with Approximations and Ensembles.
TU Darmstadt, Germany, 15.03.2016.
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| [23] | Ensembles for Unsupervised Outlier Detection: Challenges and Solutions.
Concordia University, Montreal, QC, Canada, 09.03.2016.
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| [22] | Ensembles for Unsupervised Outlier Detection: Challenges and Solutions.
University of Southern Denmark, Odense, Denmark, 03.03.2016.
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| [21] | On the Evaluation of Unsupervised Outlier Detection.
National Institute of Informatics, Tokyo, Japan, 25.02.2016.
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| [20] | Generalized Local Outlier Detection.
SnT - Interdisciplinary Centre for Security, Reliability and Trust, Luxembourg, 21.12.2015.
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| [19] | Ensembles for Unsupervised Outlier Detection: Challenges and Solutions.
ICMC, USP, São Carlos, Brazil, 25.11.2015.
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| [18] | Density-based Clustering.
University of Gothenburg, Sweden, 20.10.2015.
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| [17] | The Blind Men and the Elephant.
Workshop on Clustering in Big Data, Istituto Italiano Studi Filosofici, Palazzo Serra di Cassano, Naples, Italy, 29.05.2015.
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| [16] | The Blind Men and the Elephant.
National Institute of Informatics, Tokyo, Japan, 23.03.2015.
[ slides (pdf) ] |
| [15] | Ensemble Learning for Outlier Detection: Challenges and Solutions.
Carleton University, Ottawa, ON, Canada, 13.02.2015.
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| [14] | Challenges for Unsupervised Ensemble Learning.
Workshop: Similarity, k-NN, Dimensionality, Multimedia Databases, IRISA-INRIA, Rennes, France, 21.11.2014.
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| [13] | There and Back Again: Outlier Detection between Statistical Reasoning and Efficient Database Methods.
ICMC, USP, São Carlos, Brazil, 10.09.2014.
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| [12] | There and Back Again: Outlier Detection between Statistical Reasoning and Efficient Database Methods.
Technical University of Vienna, Austria, 15.05.2014.
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| [11] | Mind the Gap! Research in Data Mining as a Bridge Between Different Areas.
University of Vienna, Austria, 05.05.2014.
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| [10] | Challenges for Outlier Ensembles and a Subsampling-based Ensemble.
National Institute of Informatics, Tokyo, Japan, 25.03.2014.
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| [9] | Ensembles for Outlier Detection.
Aarhus University, Denmark, 15.01.2014.
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| [8] | Ensembles for Outlier Detection.
University of Copenhagen, Denmark, 07.10.2013.
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| [7] | There and Back Again: Outlier Detection between Statistical Reasoning and Efficient Database Methods.
Database Seminar Series (2012-2013) at the David R. Cheriton School of Computer Science, University of Waterloo, ON, Canada, 28.11.2012.
[ slides (pdf) ] |
| [6] | There and Back Again: Outlier Detection between Statistical Reasoning and Efficient Database Methods.
Simon Fraser University, Vancouver, BC, Canada, 16.11.2012.
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| [5] | Outlier Detection.
guest lecture in the course CMPUT 697 on Spatial Data Management and Data Mining, University of Alberta, Edmonton, AB, Canada, 28.9.+1.10.2012
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| [4] | Data Mining and the "Curse of Dimensionality".
3rd International Workshop with Mentors on Databases, Web and Information Management for Young Researchers (iDB Workshop 2011), Kyoto, Japan, 2.8.2011.
[ slides (pdf) | iDB Workshop 2011 (webpage) ] |
| [3] | Clustering Methods in High-Dimensional Spaces.
Roche Diagnostics GmbH, Penzberg, Germany, 22.7.2011.
[ slides (pdf) ] |
| [2] | Clustering in Subspaces of High-Dimensional Data.
National Institute of Informatics, Tokyo, Japan, 6.4.2010.
[ slides (pdf) ] |
| [1] | Clustering in Subspaces of High-Dimensional Data.
RWTH Aachen, Germany, 2.3.2010.
[ slides (pdf) ] |
Tutorials
| [10] | Arthur Zimek, Erich Schubert, Hans-Peter Kriegel:
Outlier Detection in High-Dimensional Data.
Tutorial at the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Gold Coast, Australia, 2013.
[ tutorial slides | tutorial webpage ] |
| [9] | Arthur Zimek, Erich Schubert, Hans-Peter Kriegel:
Outlier Detection in High-Dimensional Data.
Tutorial at the 12th IEEE International Conference on Data Mining (ICDM), Brussels, Belgium, 2012.
[ tutorial slides | tutorial webpage ] |
| [8] | Hans-Peter Kriegel, Irene Ntoutsi, Myra Spiliopoulou, Grigorios Tsoumakas, Arthur Zimek:
Mining Complex Dynamic Data.
Tutorial at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Athens, Greece, 2011.
[ abstract | webpage ] |
| [7] | Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Outlier Detection Techniques.
Tutorial at 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington, DC, 2010.
[ abstract | slides (pdf) ] |
| [6] | Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Outlier Detection Techniques.
Tutorial at 10th SIAM International Conference on Data Mining (SDM 2010), Columbus, OH, 2010.
[ abstract | slides (pdf) ] |
| [5] | Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Outlier Detection Techniques.
Tutorial at the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2009), Bangkok, Thailand, 2009.
[ slides (pdf) ] |
| [4] | Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Detecting Clusters in Moderate-to-high Dimensional Data: Subspace Clustering, Pattern-based Clustering, Correlation Clustering.
Tutorial at the 34th International Conference on Very Large Databases (VLDB 2008), Auckland, New Zealand, 2008.
[ abstract (pdf) | EE (VLDB endowment) | slides (pdf) ] |
| [3] | Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Detecting Clusters in Moderate-to-high Dimensional Data: Subspace Clustering, Pattern-based Clustering, Correlation Clustering.
Tutorial at the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2008), Las Vegas, NV, 2008.
[ slides (pdf) ] |
| [2] | Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Detecting Clusters in Moderate-to-high Dimensional Data: Subspace Clustering, Pattern-based Clustering, Correlation Clustering.
Tutorial at the 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2008), Osaka, Japan, 2008.
[ abstract | slides (pdf) ] |
| [1] | Hans-Peter Kriegel, Peer Kröger, Arthur Zimek:
Detecting Clusters in Moderate-to-high Dimensional Data: Subspace Clustering, Pattern-based Clustering, Correlation Clustering.
Tutorial at the 7th International Conference on Data Mining (ICDM 2007), Omaha, NE, 2007.
[ abstract | slides (pdf) ] |
Reviewer for Journals (selection)
Member of Program Committees (selection)
- MMM - International Conference on Multimedia Modeling, 2017
- PAKDD - Pacific Asia Conference on Knowledge Discovery and Data Mining: 2016, 2017
- SISAP - International Conference on Similarity Search and Applications: 2016
- SDM - SIAM International Conference on Data Mining: 2015, 2016
- CIKM - ACM International Conference on Information and Knowledge Management: 2013 (senior), 2014, 2015
- ECML PKDD - The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases: 2012, 2013, 2014, 2015, 2016
- SIGKDD ACM SIGKDD International Conference on Knowledge Discovery and Data Mining: 2011, 2012, 2013, 2014, 2015, 2016
Workshop and Conference Organization
Other Services
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