Dr. rer. nat. Emmanuel Müller | Karlsruhe Institute of Technology (KIT) | University of Antwerp

Research - Teaching - Short CV - Publications

Dr. rer. nat. Emmanuel Müller Senior Researcher and Lecturer Karlsruhe Institute of Technology (KIT) University of Antwerp Since July 2015, Dr. Müller is not at Karlsruhe Institute of Technology (KIT). Further information can be found on the website of Prof. Dr. Emmanuel Müller Hasso-Plattner-Institute at the University of Potsdam.

---

Research Activity

I am head of a research group with focus on data mining algorithms in heterogeneous data spaces. My group is funded by the Young Investigator Group program within the Karlsruhe Institute of Technology (KIT). As research group leader at KIT I have been awarded the status "KIT Associate Fellow", which includes the right to award doctorates. Furthermore, I am supported by a post-doctoral fellowship of the research foundation – Flanders (FWO) in collaboration with the University of Antwerp. My research interests cover efficient data mining algorithms, subspace clustering, and outlier mining in high dimensional and heterogeneous databases. I am leading the open-source initiative OpenSubspace as a general contribution to the research community. It is the basis for an evaluation study on recent data mining approaches ensuring repeatable and comparable experiments. I serve as reviewer at several international conferences and journals, as program chair of three workshops, and as guest editor for the Machine Learning journal.

Research focus:

• Efficient knowledge discovery in large and complex databases
  • Outlier mining
  • Subspace clustering
  • Graph mining 
  • Data mining in heterogeneous databases
• Applications in
  • Smart energy networks
  • Climate and environment surveillance
  • Bioinformatics
  • Business intelligence

Research projects, PhD supervision, and collaborations:

• [since 2010] Research Project: Outlier Mining in Heterogeneous Databases [overview talk]
• [since 2011] Interdisciplinary Project: Outlier Analysis on SmartMeter (Dr. Heiko Maaß)
• [since 2011] Industrial Collaboration: phi IT-Services GmbH (Prof. Michael Feindt)
• [since 2012] Research Project: Verifiable Outlier Mining  [OutRules software][ODD Workshop][ODD² Workshop][ODDx3 Workshop]
• [since 2013] Interdisciplinary Collaboration: Stream Analytics in Hydrology [CAOS project] (Dr. Sibylle Haßler & Dr. Uwe Ehret)
• [since 2014] Interdisciplinary Collaboration: Correlation Analysis in Meteorological Data (Thomas Latzko)

• [since 2012] Supervision PhD project of Hoang Vu Nguyen (with Prof. Klemens Böhm)
• [since 2011] Supervision PhD project of  Patricia Iglesias (with Prof. Klemens Böhm)
• [since 2011] Supervision PhD project of  Fabian Keller (with Prof. Klemens Böhm)
• [2010-2012] Supervision PhD project of  Andranik Khachatryan (with Prof. Klemens Böhm)

• [2006-2010] Research Project: Subspace Mining for High Dimensional Data
• [2008-2010] Research Project: Outlier Ranking Algorithms
• [2007-2009] Interdisciplinary Project: Chair of Cell Biology, RWTH Aachen (Prof. Martin Zenke)
• [2009] Industrial Collaboration: SAP Research Center, Karlsruhe (Nina Oertel)
• [2009] Industrial Collaboration: Aucos Elektronische Geräte GmbH, Aachen (Egbert König)
• [2007-2008] European Union Project: Nature Inspired Intelligent Systems
• [2008] Industrial Collaboration: National Instruments, Aachen (Stefan Romainczyk)
• [2008] Industrial Collaboration: AT&T Labs Research (Divesh Srivastava, PhD)
• [2008] Interdisciplinary Project: Virtual Reality Center, RWTH Aachen (Dr. Torsten Kuhlen)
• [2008] Interdisciplinary Project: Institute of Molecular Biotechnology,  RWTH Aachen (Dr. Kurt Hoffmann)
• [2007] Interdisciplinary Project: Chair of Pathology, RWTH Aachen (Dr. Michael Baudis)

Open source project for subspace mining:

• OpenSubspace:
  An Open Source Framework for Evaluation and Exploration of Subspace Clustering Algorithms in WEKA
  http://dme.rwth-aachen.de/OpenSubspace/
  
  OpenSubspace includes several subparts:
• A framework for subspace clustering algorithms [details in OpenSubspace and Pleiades]
• Visualization and interactive exploration of subspace clustering results [details in VISA and Morpheus]
• Fair comparison of competing subspace clustering algorithms [details in our VLDB Evaluation Study]
• Novel evaluation measures for subspace clustering results [details in E4SC]
• An extension to full space and subspace outlier ranking techniques [details in SOREX]
• Outlier descriptions assisting the verification of outliers in multiple context spaces  [details in OutRules]

• OpenSubspace is the basis for our evaluation study (VLDB 2009):
  "Evaluating Clustering in Subspace Projections of High Dimensional Data"
  http://dme.rwth-aachen.de/OpenSubspace/evaluation
  
  
• OpenSubspace includes several of our enhanced subspace clustering models and scalable algorithms:
• DUSC / INSCY as first non-redundant subspace clustering models
• EDSC as efficient density-based subspace clustering algorithm based on conservative grid-approximations
• DensEst as efficient and accurate estimation technique for frequency and density estimation in subspaces
• RESCU as global optimization for non-redundant subspace clustering (NP-hard problem)
• SSCS as a scalable approximation algorithm to the RESCU model 
• OSCLU as orthogonal subspace clustering model
• FTSC as first fault tolerant subspace clustering technique for data with missing values

Tutorials at international conferences:

• [ICDM 2010] "Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data",
  at the IEEE International Conference on Data Mining, Sydney, Australia (2010)
• [SDM 2011] "Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data",
  at the SIAM International Conference on Data Mining, Mesa, Arizona, USA (2011)
  
• [ICDE 2012] "Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data",
  at the IEEE International Conference on Data Engineering, Washington, DC, USA (2012)
• [PAKDD 2012] "Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data",
  at the Pacific-Asia Conference on Knowledge Discovery and Data Mining, Kuala Lumpur, Malaysia (2012)
• [ICML 2013] "Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data",
  at the International Conference on Machine Learning, Atlanta, USA (2013)
  
  The tutorial has been recorded during ICML 2013 and is available on techtalks.tv.
  Slides and additional information are available on our tutorial website.

Organization and editorships:

• [MultiClust 2011] "2nd MultiClust Workshop on Discovering, Summarizing and Using Multiple Clusterings"
  held in conjunction with ECML PKDD 2011, Athens, Greece 5-9 Sep. 2011
• [MultiClust 2012] "3rd MultiClust Workshop on Discovering, Summarizing and Using Multiple Clusterings"
  held in conjunction with SDM 2012, Anaheim, California, USA 26-28 Apr. 2012
• [MultiClust at MLj] "MultiClust: Discovering, Summarizing and Using Multiple Clusterings"
  as special issue of the Machine Learning journal.
• [ODD 2013] "1st Workshop on Outlier Detection and Description"
  held in conjunction with KDD 2013, Chicago, Illinois, USA 11-14 Aug. 2013
• [ODD 2014] "2nd Workshop on Outlier Detection & Description under Data Diversity"
  held in conjunction with KDD 2014, New York City, USA 24-27 Aug. 2014
• [ODD 2015] "3rd Workshop on Outlier Definition, Detection, and Description"
  held in conjunction with KDD 2015, Sydney 10-13 Aug. 2015

Services as reviewer:

• External examiner of PhD project
• Aston University, Birmingham (with Dr. Aniko Ekart)
  
  
• Program committee member at international conferences:
• SIGKDD 2013 / 2014 / 2015
  ACM Conference on Knowledge Discovery and Data Mining
• SIGMOD 2013
  ACM Conference on the Management of Data
• CIKM 2012 / 2013 / 2014 / 2015
  ACM Conference on Information and Knowledge Management
• BigData 2013 / 2014 / 2015
  IEEE International Conference on Big Data
• ICDM 2012 / 2013 / 2014
  IEEE International Conference on Data Mining
• ICDE 2013
  IEEE International Conference on Data Engineering (demo track)
• SDM 2012 / 2013 / 2014 / 2015
  SIAM International Conference on Data Mining
• ECML PKDD 2012 / 2013 / 2014 / 2015
  European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
• MultiClust 2010 / 2011 (chair) / 2012 (chair) / 2013
  Workshop on Discovering, Summarizing and Using Multiple Clusterings
• GDM 2014
  Workshop on Graph Data Management
• PTDM 2012
  Workshop on Practical Theories for Exploratory Data Mining
• 3Clust 2012
  Workshop on Multi-view data, High Dimensionality, and External Knowledge
  
  
• International journals:
• VLDB Journal (International Journal on Very Large Data Bases)
• DMKD Journal (Data Mining and Knowledge Discovery Journal – Springer)
• DKE Journal (Data & Knowledge Engineering Journal – Elsevier)
• KAIS Journal (Knowledge and Information Systems – Springer)
• SIGKDD Explorations (ACM SIGKDD Explorations)
• TKDE Journal (IEEE Transactions on Knowledge and Data Engineering)
• PAMI Journal (IEEE Transactions on Pattern Analysis and Machine Intelligence)
• TNNLS Journal (IEEE Transactions on Neural Networks and Learning Systems)
• Pattern Recognition Journal (Journal of the Pattern Recognition Society – Elsevier)
• IPL Journal (Information Processing Letters – Elsevier)
• INS Journal (Information Sciences – Elsevier)
  
  
• External reviewer at international conferences
  • KDD 2009 / 2010 
    Knowledge Discovery and Data Mining
  • SSDBM 2010 
    International Conference on Scientific and Statistical Database Management
  • SDM 2010 / 2011 
    SIAM International Conference on Data Mining
  • EDBT 2008 / 2009 / 2010 
    International Conference on Extending Database Technology
  • ICDE 2008 / 2009 / 2010 / 2015
    IEEE International Conference on Data Engineering
    

---

Teaching

at Karlsruhe Institute of Technology (KIT)

Lecturer in the course Big Data Analytics,  WS 2014/15 [slides] Awarded by the computer science department as Best Elective Lecture and as Best Tutorials (WS 2014/15) Data Mining Paradigms and Methods for Complex Databases, SS 2014 [slides] Indexing Structures for Efficient Database Access, SS 2013 [slides] Awarded by the computer science department as Best Elective Lecture (SS 2013) Data Mining Paradigms and Methods for Complex Databases, SS 2012  [slides] Data Mining Paradigms and Methods for Complex Databases, SS 2011 [slides] Supervision of lab courses: Data Warehousing and Mining, SS 2014 Successful 2nd place at DATA-MINING-CUP 2014 [press release, KIT Pressemeldung] Data Warehousing and Mining, SS 2013 Successful 3rd place at DATA-MINING-CUP 2013 [press release] Data Warehousing and Mining, SS 2012 Successful 3rd place at DATA-MINING-CUP 2012 [KIT Pressemeldung] Awarded by the computer science department as Best Lab Course (SS 2012) Development of Outlier Mining Algorithms, WS 2011/12 Students continued lab course topics, funded by two Research Student Awards Data Warehousing and Mining, SS 2011 Successful 1st place at DATA-MINING-CUP 2011 [press release, KIT Pressemeldung] Supervision of seminar and pro-seminar theses: Synergien aus Graph-Theorie und Data-Mining für die Analyse von Netzwerkdaten, WS 2013/14 Synergien aus Graph-Theorie und Data-Mining für die Analyse von Netzwerkdaten, WS 2012/13 Anonymitätsmaße und Datenanalyse am Beispiel des Smart Grid, SS 2012 Aktuelle Data-Mining Techniken für komplexe Datenbestände, WS 2011/12

at RWTH Aachen University

Lecturer in the course Advanced Data Mining Algorithms, SS 2010 Initiator of INTEGER teaching concept: INTEGER (INTEGration of Education and Research) is a concept for the integration of teaching and research. A project description, achieved results and publications are listed on the INTEGER webpage. In INTEGER several students have been supervised in an early stage of their scientific career, as part of practical lab courses or as student assistants. Currently, most of them work as research assistants and work on their PhD thesis. Exercises in the courses: Data Mining Algorithms, WS 2008/09 Advanced Data Mining Algorithms, SS 2008 Index Structures, WS 2007/08 Supervision of lab courses: Software lab "Anwendung und Evaluierung von Data Mining Techniken", SS 2009 Data Mining Algorithms, WS 2008/09 Data Mining Algorithms, WS 2007/08 Software lab "Datenstrukturen", SS 2007 Regularly supervision of seminar theses

Supervised Theses (bachelor, master and diploma theses):

• Dominik Volk, M.Sc. 
• Ornella Annicchiarico, M.Sc. (with Hoang Vu Nguyen)
• Julio De Melo Borges, M.Sc. (with Patricia Iglesias)
• Jonas Krautter, B.Sc. (with Patricia Iglesias)
• Dipl.-Math. Stefan Bertsch (with Fabian Keller)
• Dipl.-Inform. Florian Becker (with Hoang Vu Nguyen)
• Uwe Korn, B.Sc. (with Patricia Iglesias)
• Marco Neumann, B.Sc. (with Hoang Vu Nguyen)
• Dipl.-Inform. Stephan Wlotzka (with Hoang Vu Nguyen)
• Richard Molitor, B.Sc. (with Patricia Iglesias)
• Fabian Laforet, M.Sc. (with Patricia Iglesias)
• Dipl.-Inform. Jürgen Walter (with Fabian Keller)
• Andreas Wixler, M.Sc. (with Fabian Keller)
• Dipl.-Inform. Oretta Irmler (with Patricia Iglesias)
• Dipl.-Inform. Emanuel Pongracz
• Christian Stier, B.Sc. (with Andranik Khachatryan)
• Sebastian Blanc, B.Sc. (with Fabian Keller)
• Yvonne Mülle, B.Sc. (with Patricia Iglesias)

• Sebastian Raubach, B.Sc. (with Stephan Günnemann)
• Thomas Ramm, B.Sc.
• Dipl.-Inform. Charlotte Laufkötter (with Stephan Günnemann and Hardy Kremer)
• Adriola Faqolli, M.Sc. (with Marwan Hassani)
• Lingyu Wang, M.Sc.
• Dipl.-Inform. Ines Färber (with Stephan Günnemann)
• Dipl.-Inform. Matthias Schiffer
• Dipl.-Inform. Stephan Günnemann (with Ira Assent and Ralph Krieger)
• Dipl.-Inform. Babak Ahmadi (with Ira Assent and Ralph Krieger)
• Dipl.-Inform. Thorsten Wessling (with Philipp Kranen)
• Dipl.-Inform. Uwe Steinhausen (with Ira Assent and Ralph Krieger)

 

---

Short CV

• KIT Associate Fellow (since Feb. 2014)
  Formally evaluated by the department of computer science.
  Including the right to award doctorates (Promotionsrecht).
• Senior Researcher and Lecturer (since Nov. 2010)
  Institute for Program Structures and Data Organization
  Karlsruhe Institute of Technology (KIT)
• Research Assistant (Feb. 2007 - Oct. 2010)
  Chair of Computer Science 9
  RWTH Aachen University 
• Promotion [Ph.D.] (Feb. 2007 - Oct. 2010):
  • Graduated as Dr. rer. nat. at RWTH Aachen University
  • Dissertation thesis "Efficient Knowledge Discovery in Subspaces of High Dimensional Databases"
  • Graduated with distinction "summa cum laude"
• Studies (WS 2002/03 - WS 2006/07):
  • Graduated in computer science at RWTH Aachen University
  • Diplomarbeit (master thesis) "Efficient density-based subspace clustering"
  • Graduated with distinction

 

---

Publications

Listed online [DBLP Bibliography] -- [ACM Digital Library] -- [Microsoft Academic Search] -- [Google Scholar]

2015	Müller E., Assent I., Günnemann S., Seidl T., Dy J.: Editorial: MultiClust Special Issue on Discovering, Summarizing and Using Multiple Clusterings Machine Learning Journal, Springer (January 2015) [ML Journal] Khachatryan A., Müller E., Stier C., Böhm K.: Improving Accuracy and Robustness of Self-Tuning Histograms by Subspace Clustering IEEE Transactions on Knowledge and Data Engineering  Journal (2015) [TKDE Journal] Iglesias P., Müller E., Korn U., Böhm K., Kappes A., Hartmann T., Wagner D.: Efficient Algorithms for a Robust Modularity-Driven Clustering of Attributed Graphs Proc. SIAM International Conference on Data Mining (SDM 2015), Vancouver, Canada (2015) [SDM 2015][Full Text PDF] Keller F., Müller E., Böhm K.: Estimating Mutual Information on Data Streams Proc. 27th International Conference on Scientific and Statistical Database Management (SSDBM 2015), San Diego, USA (2015)  [SSDBM 2015][Full Text PDF] Nguyen H. V., Böhm K., Becker F., Goldman B., Hinkel G., Müller E.: Identifying User Interests within the Data Space - a Case Study with SkyServer Proc. 18th International Conference on Extending Database Technology (EDBT 2015), Brussels, Belgium (2015) [EDBT 2015][Full Text PDF]
2014	Nguyen H. V. Müller E., Böhm K.: A Near-Linear Time Subspace Search Scheme for Unsupervised Selection of Correlated Features Big Data Research Journal, Elsevier (2014) [BDR Journal][Full Text PDF] Nguyen H. V. Müller E., Vreeken J., Böhm K.: Unsupervised Interaction-Preserving Discretization of Multivariate Data Data Mining and Knowledge Discovery Journal, Springer (2014) [DMKD Journal][ECML PKDD 2014] Perozzi B., Akoglu L., Iglesias P., Müller E.: Focused Clustering and Outlier Detection in Large Attributed Graphs Proc. 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2014), New York City, USA (2014) (full paper acceptance rate 14.6%) [KDD 2014][Full Text PDF] Nguyen H. V., Müller E., Vreeken J., Efros P., Böhm K.: Multivariate Maximal Correlation Analysis Proc. International Conference on Machine Learning (ICML 2014), Beijing China (2014) [ICML 2014] [Full Text PDF] Iglesias P., Müller E., Irmler O., Böhm K.: Local Context Selection for Outlier Ranking in Graphs with Multiple Numeric Node Attributes Proc. 26th International Conference on Scientific and Statistical Database Management (SSDBM 2014), Aalborg, Denmark (2014)  [SSDBM 2014][Full Text PDF] Nguyen H. V., Müller E., Andritsos P., Böhm K.: Detecting Correlated Columns in Relational Databases with Mixed Data Types Proc. 26th International Conference on Scientific and Statistical Database Management (SSDBM 2014), Aalborg, Denmark (2014)  [SSDBM 2014][Full Text PDF]
2013	Akoglu L., Müller E., Vreeken J. (Eds.): Proceedings of the KDD 2013 Workshop on Outlier Detection and Description ACM SIGKDD Workshop Proceedings of the 1st Workshop on Outlier Detection and Description (ODD 2013) [ODD @ KDD 2013] [Proceedings] Eichinger F., Pathmaperuma D., Vogt H., Müller E.: Data Analysis Challenges in the Future Energy Domain Yu T., Chawla N., Simoff S. (eds.): Computational Intelligent Data Analysis for Sustainable Development, Chapman and Hall/CRC (2013)  [DMKD Series][Full Text PDF] Iglesias P., Müller E., Laforet F., Keller F., Böhm K.: Statistical Selection of Congruent Subspaces for Mining Attributed Graphs Proc. IEEE International Conference on Data Mining (ICDM 2013), Dallas, TX, USA (2013) (full paper acceptance rate 11.6%) [ICDM 2013][Full Text PDF] Aksehirli E., Goethals B., Müller E., Vreeken J.: Cartification: A Neighborhood Preserving Transformation for Mining High Dimensional Data Proc. IEEE International Conference on Data Mining (ICDM 2013), Dallas, TX, USA (2013) (acceptance rate 19.6%) [ICDM 2013][Full Text PDF] Nguyen H. V., Müller E., Böhm K.: 4S: Scalable Subspace Search Scheme Overcoming Traditional Apriori Processing Proc. IEEE International Conference on Big Data (BigData 2013), Santa Clara, CA, USA (2013) (full paper acceptance rate 17.4%) [BigData 2013][Full Text PDF] Keller F., Müller E., Wixler A., Böhm K.: Flexible and Adaptive Subspace Search for Outlier Analysis Proc. 22nd ACM International Conference on Information and Knowledge Management (CIKM 2013), San Francisco, USA (2013) (full paper acceptance rate 16.9%) [CIKM 2013][Full Text PDF] Nguyen H. V., Müller E., Vreeken J., Keller F., Böhm K.: CMI: An Information-Theoretic Contrast Measure for Enhancing Subspace Cluster and Outlier Detection Proc. SIAM International Conference on Data Mining (SDM 2013), Austin, Texas, USA (2013) [SDM 2013][Full Text PDF] Müller E., Iglesias P., Mülle Y., Böhm K.: Ranking Outlier Nodes in Subspaces of Attributed Graphs Proc. 4th International Workshop on Graph Data Management: Techniques and Applications (GDM 2013) in conjunction with IEEE 29th International Conference on Data Engineering (ICDE 2013), Brisbane, Australia (2013) [ICDE 2013] [GDM 2013]
2012	Müller E., Seidl T., Venkatasubramanian S., Zimek A. (Eds.): Proceedings of the 3rd MultiClust Workshop SIAM Workshop Proceedings of the 3rd MultiClust Workshop: Discovering, Summarizing and Using Multiple Clusterings (MultiClust 2012) [MultiClust 2012] [Proceedings] Müller E., Assent I., Iglesias P., Mülle Y., Böhm K.: Outlier Ranking via Subspace Analysis in Multiple Views of the Data Proc. IEEE International Conference on Data Mining (ICDM 2012), Brussels, Belgium (2012) (full paper acceptance rate 10.7%) [ICDM 2012][Full Text PDF] Keller F., Müller E., Böhm K.: HiCS: High Contrast Subspaces for Density-Based Outlier Ranking Proc. IEEE 28th International Conference on Data Engineering (ICDE 2012), Washington, DC, USA (2012)  [ICDE 2012][Full Text PDF][Supplementary material] Müller E., Günnemann S., Färber I., Seidl T.: Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data Tutorial at IEEE 28th International Conference on Data Engineering (ICDE 2012), Washington, DC, USA. (2012) [ICDE 2012][Full Text PDF][Tutorial Website] Müller E., Günnemann S., Färber I., Seidl T.: Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data Tutorial at 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2012), Kuala Lumpur, Malaysia. (2012) [PAKDD 2012][Tutorial Website] Khachatryan A., F., Müller E., Stier C., Böhm K.: Sensitivity of Self-Tuning Histograms: Query Order Affecting Accuracy and Robustness Proc. 24th International Conference on Scientific and Statistical Database Management (SSDBM 2012), Chania, Crete, Greece (2012)  [SSDBM 2012] Maaß H., Çakmak H. K., Süss W., Quinte A., Jakob W., Müller E., Böhm K., Stucky K. U., Kühnapfel U.: Introducing a New Voltage Time Series Approach for Electrical Power Grid Analysis Proc. IEEE International Energy Conference & Exhibition (EnergyCon 2012), Florence, Italy (2012)  [EnergyCon 2012] Vanea A., Müller E., Keller F., Böhm K.: Instant Selection of High Contrast Projections in Multi-dimensional Data Streams Proc. Workshop on Instant Interactive Data Mining (IID 2012) in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2012), Bristol, UK (2012)  [IID 2012][Full Text PDF] Müller E., Keller F., Blanc S., Böhm K.: OutRules: A Framework for Outlier Descriptions in Multiple Context Spaces Proc. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2012), Bristol, UK (2012) (Demo) [ECML PKDD 2012][OutRules Project] Keller F., Müller E., Böhm K.: Υποχώροι Υψηλής Αντίθεσης για την Βαθμολόγηση Εκτόπων με Βάση την Πυκνότητα Proc. Hellenic Data Management Symposium (HDMS 2012), Chania, Crete, Greece (2012)  [HDMS 2012]
2011	Müller E., Günnemann S., Assent I., Seidl T. (Eds.): Proceedings of the 2nd MultiClust Workshop CEUR Workshop Proceedings of the 2nd MultiClust Workshop: Discovering, Summarizing and Using Multiple Clusterings (MultiClust 2011) [MultiClust 2011][Proceedings] Müller E., Assent I., Günnemann S., Seidl T.: Scalable Density-Based Subspace Clustering Proc. 20th ACM International Conference on Information and Knowledge Management (CIKM 2011), Glasgow, UK (2011) (full paper acceptance rate 15%) [CIKM 2011][Full Text PDF] Günnemann S., Färber I., Müller E., Assent I., Seidl T.: External Evaluation Measures for Subspace Clustering Proc. 20th ACM International Conference on Information and Knowledge Management (CIKM 2011), Glasgow, UK (2011) (full paper acceptance rate 15%) [CIKM 2011][Full Text PDF] Müller E., Schiffer M., Seidl T.: Statistical Selection of Relevant Subspace Projections for Outlier Ranking Proc. IEEE 27th International Conference on Data Engineering (ICDE 2011), Hannover, Germany (2011) (full paper acceptance rate 19.8%) [ICDE 2011][Full Text PDF] Günnemann S., Müller E., Raubach S., Seidl T.: Flexible Fault Tolerant Subspace Clustering Proc. IEEE International Conference on Data Mining (ICDM 2011), Vancouver, Canada (2011) (full paper acceptance rate 12.2%) [ICDM 2011][Full Text PDF] Müller E., Günnemann S., Färber I., Seidl T.: Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data Tutorial at SIAM International Conference on Data Mining (SDM 2011), Mesa, Arizona, USA. (2011) [SDM 2011][Full Text PDF][Tutorial Website][Tutorial Slides] Khachatryan A. , Müller E., Böhm K., Kopper J.: Efficient Selectivity Estimation by Histogram Construction based on Subspace Clustering Proc. 23rd International Conference on Scientific and Statistical Database Management (SSDBM 2011), Portland, Oregon, USA (2011) [SSDBM 2011]   Müller E., Assent I., Günnemann S., Gerwert P., Hannen M., Jansen T., Seidl T.: A Framework for Evaluation and Exploration of Clustering Algorithms in Subspaces of High Dimensional Databases Proc. 14th GI Conference on Database Systems for Business, Technology, and the Web (BTW 2011), Kaiserslautern, Germany (2011) [BTW 2011][Full Text PDF] Müller E., Schiffer M., Seidl T.: Στατιστική Επιλογή από Σημαντικούς Υποχώρους για Εύρεση Εκτόπων Proc. Hellenic Data Management Symposium (HDMS 2011), Athens, Greece (2011) [HDMS 2011]
2010	Müller E.: Efficient Knowledge Discovery in Subspaces of High Dimensional Databases Dissertation, Fakultät für Mathematik, Informatik und Naturwissenschaften, RWTH Aachen University. (2010) Tag der mündlichen Prüfung: 09.06.2010 [RWTH Bibliothek] Müller E., Günnemann S., Färber I., Seidl T.: Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data Tutorial at IEEE International Conference on Data Mining (ICDM 2010), Sydney, Australia (2010) [ICDM 2010][Full Text PDF][Tutorial Website][Tutorial Slides] Kranen P., Müller E., Assent I., Krieger R., Seidl T.: Incremental Learning of Medical Data for Multi-Step Patient Health Classification Plant C., Böhm C. (eds.): Database Technology for Life Sciences and Medicine, World Scientific Publishing P.321-344 (2010) [World Scientific Publishing ] Müller E., Schiffer M., Seidl T.: Adaptive Outlierness for Subspace Outlier Ranking Proc. 19th ACM Conference on Information and Knowledge Management (CIKM 2010), Toronto, Canada P.1629-1632 (2010) [CIKM 2010][Full Text PDF] Müller E., Kranen P., Nett M., Reidl F., Seidl T.: Air-Indexing on Error Prone Communication Channels Proc. of the 15th International Conference on Database Systems for Advanced Applications (DASFAA 2010), Tsukuba, Japan, Springer LNCS 5981 P.505-519 (2010) [DASFAA 2010] Hassani M., Müller E., Spaus P., Faqolli A., Palpanas T., Seidl T.: Self-Organizing Energy Aware Clustering of Nodes in Sensor Networks Using Relevant Attributes Proc. 4th International Workshop on Knowledge Discovery from Sensor Data (SensorKDD 2010) in conjunction with 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington, DC, USA P.87-96 (2010) [SensorKDD 2010] Müller E.: Mining Subspace Clusters: Enhanced Models, Efficient Algorithms and an Objective Evaluation Study PhD Workshop of the 36th International Conference on Very Large Data Bases (VLDB 2010), Singapore (2010) [VLDB 2010] [Full Text PDF] Färber I., Günnemann S., Kriegel H.-P., Kröger P., Müller E., Schubert E., Seidl T., Zimek A.: On Using Class-Labels in Evaluation of Clusterings Proc. 1st International Workshop on Discovering, Summarizing and Using Multiple Clusterings (MultiClust 2010) in conjunction with 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington, DC, USA (2010) [MultiClust 2010] [Full Text PDF] [Talk Slides] Günnemann S., Färber I., Müller E., Seidl T.: ASCLU: Alternative Subspace Clustering Proc. 1st International Workshop on Discovering, Summarizing and Using Multiple Clusterings (MultiClust 2010) in conjunction with 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington, DC, USA (2010) [MultiClust 2010] [Full Text PDF] [Talk Slides] Assent I., Müller E., Günnemann S., Krieger R., Seidl T.: Less is More: Non-Redundant Subspace Clustering Proc. 1st International Workshop on Discovering, Summarizing and Using Multiple Clusterings (MultiClust 2010) in conjunction with 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2010), Washington, DC, USA (2010) [MultiClust 2010] [Full Text PDF] [Talk Slides] Müller E., Schiffer M., Gerwert P., Hannen M., Jansen T., Seidl T.: SOREX: Subspace Outlier Ranking Exploration Toolkit Proc. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2010), Barcelona, Spain, Springer, LNAI 6323 P.607-610 (2010) (Demo) [ECML PKDD 2010][SOREX Project] Meyer U., Müller E., Seidl T.: Sichere und energieeffiziente Mobilfunkkommunikation: Energieeffiziente Lösungen für sichere Datenübertragung in zukünftigen mobilen Kommunikationsgeräten RWTH Themen 1/2010: Erste Ergebnisse der Exzellenzinitiative P.36-38 (2010) [RWTH-Themen]
2009	Müller E., Günnemann S., Assent I., Seidl T.: Evaluating Clustering in Subspace Projections of High Dimensional Data Proc. 35th International Conference on Very Large Data Bases (VLDB 2009), Lyon, France, PVLDB Journal, Vol. 2, No. 1, P.1270-1281 (2009) (Experiments and Analyses track, acceptance rate 23.1%) [VLDB 2009] [Full Text PDF] [Supplementary material] Müller E., Assent I., Günnemann S., Krieger R., Seidl T.: Relevant Subspace Clustering: Mining the Most Interesting Non-Redundant Concepts in High Dimensional Data Proc. IEEE International Conference on Data Mining (ICDM 2009), Miami, USA P.377-386 (2009) (full paper acceptance rate 8.9%) [ICDM 2009][Full Text PDF][Supplementary material] Müller E., Assent I., Krieger R., Günnemann S., Seidl T.: DensEst: Density Estimation for Data Mining in High Dimensional Spaces Proc. SIAM International Conference on Data Mining (SDM 2009), Sparks, Nevada, USA. P.173-184 (2009) (full paper acceptance rate 15.6%) [SDM 2009][Full Text PDF] Günnemann S., Müller E., Färber I., Seidl T.: Detection of Orthogonal Concepts in Subspaces of High Dimensional Data Proc. 18th ACM Conference on Information and Knowledge Management (CIKM 2009), Hong Kong, China P.1317-1326 (2009) (full paper acceptance rate 14.5%) [CIKM 2009] [Full Text PDF] Müller E., Assent I., Seidl T.: HSM: Heterogeneous Subspace Mining in High Dimensional Data Proc. 21st International Conference on Scientific and Statistical Database Management (SSDBM 2009), New Orleans, Louisiana, USA P.497-516 (2009) [SSDBM 2009] Wang L., Oertel N., Müller E., Seidl T.: Counterfeit Detection by Extracting Rules from Product Traces Proc. 12th IASTED International Conference on Intelligent Systems and Control (ISC 2009), Cambridge, USA (2009) [IASTED ISC 2009] Hassani M., Müller E., Seidl T.: EDISKCO: Energy Efficient Distributed In-Sensor-Network K-center Clustering with Outliers Proc. 3rd International Workshop on Knowledge Discovery from Sensor Data (SensorKDD 2009) in conjunction with 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2009), Paris, France P.39-48 (2009) [SensorKDD 2009][Full Text PDF] Müller E., Assent I., Günnemann S., Jansen T., Seidl T.: OpenSubspace: An Open Source Framework for Evaluation and Exploration of Subspace Clustering Algorithms in WEKA Proc. 1st Open Source in Data Mining Workshop (OSDM 2009) in conjunction with 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2009), Bangkok, Thailand P.2-13 (2009) [OSDM 2009][Full Text PDF][OpenSubspace Project] Schiffer M., Müller E., Seidl T.: SubRank: Ranking Local Outliers in Projections of High-Dimensional Spaces Datenbank-Spektrum Vol. 9 Issue 29 P.53-55 (2009) (BTW-Studierendenprogramm) [DB Spektrum][Full Text PDF]
2008	Assent I., Krieger R., Müller E., Seidl T.: INSCY: Indexing Subspace Clusters with In-Process-Removal of Redundancy Proc. IEEE International Conference on Data Mining (ICDM 2008), Pisa, Italy P.719-724 (2008) (acceptance rate 20%) [ICDM 2008][Full Text PDF] Assent I., Krieger R., Müller E., Seidl T.: EDSC: Efficient Density-Based Subspace Clustering Proc. ACM 17th Conference on Information and Knowledge Management (CIKM 2008), Napa Valley, USA P.1093-1102 (2008) (full paper acceptance rate 17%) [CIKM 2008][Full Text PDF] Müller E., Assent I., Steinhausen U., Seidl T.: OutRank: ranking outliers in high dimensional data Proc. 2nd International Workshop on Ranking in Databases (DBRank 2008) in conjunction with IEEE 24th International Conference on Data Engineering (ICDE 2008), Cancun, Mexico P.600-603 (2008) [ICDE 2008] [DBRank 2008][Full Text PDF] Müller E., Assent I., Krieger R., Jansen T., Seidl T.: Morpheus: Interactive Exploration of Subspace Clustering Proc. 14th ACM SIGKDD International Conference on Knowledge Discovery in Databases (KDD 2008), Las Vegas, USA P.1089-1092 (2008) (Demo) [KDD 2008][Full Text PDF] Assent I., Müller E., Krieger R., Jansen T., Seidl T.: Pleiades: Subspace Clustering and Evaluation Proc. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2008), Antwerp, Belgium, Springer LNCS 5212. P.666-671 (2008) (Demo) [ECML PKKD 2008] [Springer LNCS 5212] Kranen P., Kensche D., Kim S., Zimmermann N., Müller E., Quix C., Li X., Gries T., Seidl T., Jarke M., Leonhardt S.: Mobile Mining and Information Management in HealthNet Scenarios Proceedings of the 9th IEEE MDM International Conference on Mobile Data Management (MDM 2008), Beijing, China P.215-216 (2008) (Demo) [MDM 2008] Müller E., Kranen P., Nett M., Reidl F., Seidl T.: A General Framework for Data Dissemination Simulation for Real World Scenarios Proceedings of the 14th ACM SIGMOBILE International Conference on Mobile Computing and Networking (MobiCom 2008), San Francisco, USA (2008) (Demo) [MobiCom 2008] Ruau D., Kolarik C., Mevissen H.-T., Müller E., Assent I., Krieger R., Seidl T., Hofmann-Apitius M., Zenke M.: Public microarray repository semantic annotation with ontologies employing text mining and expression profile correlation BMC Bioinformatics 2008, 9(Suppl 10):O5 doi:10.1186/1471-2105-9-S10-O54th ISCB Student Council Symposium in conjunction with International Conference Intelligent Systems for Molecular Biology (ISMB 2008), Toronto, Canada (2008) (poster and oral presentation) [ISCB 2008] [ISMB 2008] Kim S., Leonhardt S., Zimmermann N., Kranen P., Kensche D., Müller E., Quix C.: Influence of contact pressure and moisture on the signal quality of a newly developed textile ECG sensor shirt 5th International Workshop on Wearable and Implantable Body Sensor Networks (BSN 2008), Hong Kong, China (2008) [BSN 2008] Seidl T., Müller E., Assent I., Steinhausen U.: Outlier detection and ranking based on subspace clustering Dagstuhl Seminar 08421 on Uncertainty Management in Information Systems. (2008) [Dagstuhl Seminar] [Full Text PDF]
2007	Assent I., Krieger R., Müller E., Seidl T.: VISA: Visual Subspace Clustering Analysis ACM SIGKDD Explorations Special Issue on Visual Analytics, Vol. 9, Issue 2 P.5-12 (2007) [SIGKDD Explorations] [Full Text PDF] Assent I., Krieger R., Müller E., Seidl T.: DUSC: Dimensionality Unbiased Subspace Clustering Proc. IEEE International Conference on Data Mining (ICDM 2007), Omaha, Nebraska, USA P.409-414 (2007) (acceptance rate 19%) [ICDM 2007][Full Text PDF] Müller E.: Density-based clustering in arbitrary subspaces Proc. Workshop on Nature-inspired Methods for Local Pattern Detection (NiLOP 2007) in conjunction with NiSIS 2007, St. Julians, Malta (2007) Assent I., Krieger R., Müller E., Steffens A., Seidl T.: Evolutionary Subspace Search in biologically-inspired Optimal Niches Proc. Annual Symposium on Nature inspired Smart Information Systems (NiSIS 2007), St Julians, Malta (2007) [NiSIS 2007] Assent I., Krieger R., Müller E., Seidl T.: Removing Dimensionality Bias in Density-based Subspace Clustering Abstract in Dutch-Belgian Data Base Day (DBDBD 2007), Eindhoven, NL (2007) [DBDBD 2007] Aleksandrowicz A., Kensche D., Kim S., Kranen P., Müller E., Quix C.: Mobile and Wearable P2P Information Management in HEALTHNET Applications IEEE Benelux Chapter on Engineering in Medicine and Biology (EMB) (2007) Assent I., Krieger R., Müller E., Seidl T.: Subspace outlier mining in large multimedia databases In: M. Berthold, K. Morik, A. Siebes(eds.): Parallel Universes and Local Patterns, Dagstuhl Seminar 07181 (2007) [Dagstuhl Seminar] [Full Text PDF] Müller E.: Subspace Clustering für die Analyse von CGH Daten Studierendenprogramm at the 12th GI-conference on Databases, Technology and Web (BTW 2007), Aachen, Germany: 31-33 (2007) [BTW 2007] [BTW Studierendenprogramm][Full Text PDF]
2006	Möllers M., Müller E., Neider D., Seweryn L.: MediSign - Secure Pharmaceutic Distribution GI Informatiktage 31. März - 01. April 2006 in Bonn P.113-115 (2006) [Informatiktage][Full Text PDF]