Stefan Rüping
About
Dr. Stefan Rüping leades the business field of Big Data Analytics
at the Fraunhofer Institute IAIS.
He has years of experience in consulting, project management, and teaching in both industrial and academia projects.
His research interests include machine learning, artificial intelligence, knowledge discovery and data mining.
Before joining Fraunhofer he was working as a research
assistant and Ph. D. student at the
Artificial Intelligence Chair of the
University of Dortmund, where
he finished his Ph. D. in 2006 as a student of
Prof.
Katharina Morik.
[Researchgate profile]
In the news
Publications
2015 |
Rüping, Stefan: Big Data in Medizin and Gesundheitswesen. In: Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz,58(8), pp. 794-798, 2015. |
2014 |
Tsiliki, Georgia and Kossida, Sophia and Friesen, Natalja and Rüping, Stefan and Tzagarakis, Manolis and Karacapilidis, Nikos: A Data Mining Based Approach for Collaborative Analysis of Biomedical Data. In: International Journal on Artificial Intelligence Tools, 23(4), 2014. |
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Friesen, Natalja and Kindermann, Jörg and Maassen, Doris and Rüping, Stefan: Data Mining in Data-Intensive and Cognitively-Complex Settings: Lessons Learned from the Dicode Project. In: Mastering Data-Intensive Collaboration and Decision Making, Karacapilidis, Nikos (ed.), pp. 201-212, Springer, 2014. |
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Friesen, Natalja and Jakob, Max and Kindermann, Jörg and Maassen, Doris and Poigné, Axel and Rüping, Stefan and Trabold, Daniel: The Dicode Data Mining Services. In: Mastering Data-Intensive Collaboration and Decision Making, Karacapilidis, Nikos (ed.), pp. 89-118, Springer, 2014. |
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Kondylakis, Haridimos and Koumakis, Lefteris and Rüping, Stefan and Kazantzaki, Eleni and Marias, Kostas and Tsiknakis, Manolis: PMIR: A Personal Medical Information Recommender. In: Proceedings of MIE2014, the 25th European Medical Informatics Conference, Istanbul, Turkey, August 31 - September 3, p. 1193, 2014. |
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Christ-Neumann, Marie-Luise and Escrich, Ana and Anguita, Alberto and Stenzhorn, Holger and Taylor, Marian and Ramay, Hena and Rüping, Stefan and Krauth, Christian and Kuchinke, Wolfgang and Graf, Norbert and Rossi, Simona:
Usability on the p-medicine infrastructure: an extended usability concept.. In: ecancermedicalscience, 8(1), p. 399, 2014.
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2013 |
Rüping, Stefan and Anguita, Alberto
and Bucur, Anca and Cirstea, Traian Cristian and Jacobs, Björn and
Torge, Antje: Improving
the Implementation of Clinical Decision Support Systems. In:
Proceedings of 35th Annual International Conference of the IEEE
Engineering in Medicine and Biology Society (EMBC’13), Osaka, Japan, 2013. |
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Rüping, Stefan and Graf, Norbert:
Datenanalyse: Big Data in der Medizin. In: Dtsch Arztebl International, 110(41), 2013.
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Stamatakos, Georgios and Dionysiou, Dimitra and Lunzer, Aran and Belleman, Robert and Kolokotroni, Eleni and Georgiadi, Eleni and Erdt, Marius and Pukacki, Juliusz and Rüping, Stefan and Giatili, Stavroula and d'Onofrio, Albert and Sfakianakis, Stelios and Marias, Kostas and Desmedt, Christine and Tsiknakis, Manolis and Graf, Norbert: The Technologically Integrated Oncosimulator: Combining Multiscale Cancer Modeling With Information Technology in the In Silico Oncology Context. In: IEEE Journal of Biomedical and Health Informatics, 18(3), pp. 840-54, 2014. |
2012 |
Grosskreutz, Henrik and Paurat, Daniel
and Rüping,
Stefan: An Enhanced
Relevance Criterion for More Concise Supervised Pattern
Discovery. In: Proceedings of the 18th ACM SIGKDD Conference on
Knowledge Discovery and Data Mining (KDD 2012), Beijung, China, 2012.
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Friesen, Natalja and Rüping,
Stefan:
Distance Metric Learning for Recommender
Systems in Complex. In: Domains Mastering Data-Intensive Collaboration
through the Synergy of Human and Machine Reasoning (dicoSyn 2012),
workshop at CSCW 2012, February 12, 2012, Seattle, WA, 2012.
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Tsiliki, Georgia and Kossida, Sophia and
Friesen, Natalja and Rüping, Stefan and Tzagarakis, Manolis and
Karacapilidis, Nikos:Data Mining Based Collaborative
Analysis of Microarray Data. In: IEEE 24th International
Conference on Tools with Artificial Intelligence (ICTAI),
p. 682-689, 2012.
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Karacapilidis, Nikos and Rüping,
Stefan and Tsiliki, Georgia and Tzagarakis, Manolis: Towards a
Meaningful Analysis of Big Data - Enhancing Data Mining Techniques
through a Collaborative Decision Making Environment.
DATA 2012, p. 141-146, 2012.
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Karacapilidis, Nikos and Lau, Lydia
and Lee, C. and Rüping, Stefan:
Mastering data-intensive collaboration through the synergy of human and
machine reasoning.
In:
S.E. Poltrock, C. Simone, J. Grudin, G. Mark and J. Riedl (eds.),
Proceedings of the 2012 ACM Conference on Computer Supported Cooperative
Work (CSCW 2012) - Companion Volume, Seattle, WA, USA, February 11-15,
ACM Press, pp. 21-22, 2012.
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Graf, Norbert et al.: P-medicine: a solution for translational research? In: Pediatric Blood and Cancer, 2012.
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2011 |
Bucur, Anca and Rüping,
Stefan and Sengstag, Thierry and Sfakianakis, Stelios and Wegener, Dennis:
The ACGT project in retrospect: Lessons learned and future
outlook. In: Proceedings of the International Conference on
Computational Science (ICCS 2011), Procedia Computer Science, Volume
4, Pages 1119-1128, 2011.
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Wegener, Dennis, and Anguita, Alberto, and
Rüping,
Stefan: Enabling the reuse
of data mining processes in
healthcare by integrating data semantics. In: Proceedings of the 3th
International Workshop on Knowledge Representation for Health Care,
KR4HC, Bled, Slovenia, 2011.
pp.222-235
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Wegener, Dennis and Rüping, Stefan
Integration and reuse of data mining in business processes - A pattern-based approach. In: International journal of business process integration and management : IJBPIM 5 (2011), No.3, pp.218-228.
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Rossi, Simona, and Christ-Neumann,
Marie-Luise, and Rüping, Stefan and Buffa, Francesca, and
Wegener, Dennis, and McVie, Gordon, and Coveney, Peter, and Graf,
Norbert, and Delorenzi, Mauro.
p-Medicine: From data
sharing and integration via VPH models to personalized
medicine. In: Ecancermedicalscience. Online journal 5 (2011),
Art. 218, 6 pp, 2011.
http://www.ecancermedicalscience.com.
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Wegener, Dennis, and Rossi, Simona, and
Buffa, Francesca, and Delorenzi, Mauro, and Rüping, Stefan
Towards an environment
for data mining based analysis processes in bioinformatics &
personalized medicine. In: IEEE International Conference
on Bioinformatics and Biomedicine Workshops, BIBMW 2011, 12-15
November 2011, Atlanta, GA, USA, pp.570-577, 2011.
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2010 |
Friesen, Natalja and Rüping,
Stefan:
Workflow Analysis
Using Graph Kernels. In: Proceedings of the ECML/PKDD Workshop
on Third-Generation Data Mining: Towards Service-Oriented Knowledge
Discovery (SoKD’10), Barcelona, Spain, 2010.
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Rüping, Stefan and Wegener, Dennis,
and Bremer, Philipp:
Re-using Data Mining
Workflows. In: Proceedings of the ECML/PKDD Workshop on
Third-Generation Data Mining: Towards Service-Oriented Knowledge
Discovery (SoKD’10), Barcelona, Spain, 2010.
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Grosskreutz, Henrik, and Lemmen,
Benedikt, and Rüping, Stefan:
Secure Top-k
Subgroup Discovery. In: Proceedings of the ECML/PKDD Workshop on
Privacy and Security issues in Data Mining and Machine Learning
(PSDML 2010), Barcelona, Spain, 2010.
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Grosskreutz, Henrik, and Lemmen,
Benedikt, and Rüping, Stefan:
Privacy-preserving data-mining. In: Informatik-Spektrum, Bd.33
(2010), 4, 2010. |
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Wegener, Dennis and Rüping,
Stefan:On
Reusing Data Mining in Business Processes - A Pattern-based
Approach. In: Proceedings of the 1st International Workshop on
Reuse in Business Process Management (rBPM 2010), Hoboken, New Jersey,
USA, 2010.
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Rüping, Stefan:
SVM Classifier Estimation from
Group Probabilities.
In: Proceedings of the 27th International Conference on Machine
Learning (ICML 2010), Haifa, Israel, 2010.
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Wegener, Dennis and Rüping,
Stefan: On Integrating
Data Mining into Business Processes. In: Proceedings of the 13th
International Conference on Business Information Systems (BIS 2010),
Berlin, Germany, 2010.
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2009 |
Tagaris, A. and Konnis, G. and Benetou,
X. and Dimakopoulos, T. and Kassis, K. and Athanasiadis, N. and
Rüping, S. and Grosskreutz, H. and Koutsouris,
D.: Integrated Web Services
Platform for the facilitation of fraud detection in health care
e-government services. In: Proceedings of the 9th International
Conference on Information Technology and Applications in Biomedicine
(ITAB 2009), Lacarna, Cyprus, 2009.
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Grosskreutz, Henrik and Rüping,
Stefan: On
Subgroup Discovery in Numerical
Domains. In: Data
Mining and Knowledge Discovery, 19(2), 210-226, 2009.
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Rüping,
Stefan: Ranking
Interesting Subgroups. In: Proceedings of the 26th International
Conference on Machine Learning (ICML 2009), Bottou, Leon and Littman,
Michael (Eds.), Montreal, Omnipress, 913-920, 2009.
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Seth, Shivani, Rüping, Stefan, and Wrobel,
Stefan: Metadata Extraction
Using Text Mining. In: Healthgrid Research,
Innovation and Business Case - Proceedings of HealthGrid 2009,
Solomonides, Tony, Hofmann-Apitius, Martin, Freudigmann, Mathias, Semler,
Sebastian Claudius, Legre, Yannick, and Kratz, Mary (eds.), IOS Press,
95-104, 2009.
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Rüping, Stefan, Wegener, Dennis,
Sfakianakis, Stelios and Sengstag, Thierry:
Workflows for
Intelligent Monitoring Using Proxy Services. In: Healthgrid Research,
Innovation and Business Case - Proceedings of HealthGrid 2009,
Solomonides, Tony, Hofmann-Apitius, Martin, Freudigmann, Mathias, Semler,
Sebastian Claudius, Legre, Yannick, and Kratz, Mary (eds.), IOS Press,
277-282, 2009.
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Wegener, Dennis, Sengstag, Thierry,
Sfakianakis, Stelios, Rüping,
Stefan, Assi, Anthony: GridR:
An R-based tool for scientific data analysis in grid
environments. In: Future
Generation Computer Systems: The International Journal of Grid Computing:
Theory, Methods and Applications, 25(4), 481-488, 2009.
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Sfakianakis, Stelios, Graf, Norbert, Hoppe,
Aleaxander, Rueping, Stefan, Wegener, Dennis, and Koumakis,
Lefteris: Building a
System for Advancing Clinico-Genomic Trials on Cancer. In:
Bassiliades, N. (ed.), Proceedings
of the Workshops of the 5th IFIP Conference on Artificial Intelligence
Applications & Innovations (AIAI-2009), Thessaloniki, Greece,
April 23-25, pp. 36-47, 2009.
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2008 |
Rüping,
Stefan. Globalization of Local
Models with SVMs. In: LeGo-08 - From Local Patterns to Global
Models, Workshop at ECML/PKDD 08, 2008.
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Grosskreutz, Henrik, Rüping, Stefan
and Wrobel, Stefan.
Tight Optimistic
Estimates for Fast Subgroup Discovery.
In: Proceedings of the
European Conference on Machine Learning and Principles and Practice of
Knowledge Discovery in Databases,
Springer LNAI, 2008.
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Rüping, Stefan, Punko, Natalja, Günter, Björn and
Grosskreutz, Henrik.
Procurement Fraud Discovery
using Similarity Measure Learning.
In: Transactions on Case-based Reasoning, 1(1), 37-46, 2008.
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Rüping, Stefan, Punko, Natalja, Günter, Björn and
Grosskreutz, Henrik.
Procurement Fraud Discovery
using Similarity Measure Learning.
In: Advances in Data Mining - Poster and Workshop Proceedings of the 8th
Industrial Conference on Data Mining, I. Bechindaritz, P. Perner and
L. Shapiro (eds.), 2008.
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Punko, Natalja, Rüping, Stefan and
Wrobel,
Stefan. Facilitating
Clinico-Genomic Knowledge Discovery by Automatic Selection of KDD
Processes.
ICML 2008 Workshop on Machine Learning for Health Care Applications,
Helsinki, Finland, July 9, 2008.
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Wegener, Dennis and Sengstag, Thierry and Sfakianakis, Stelios and
Rüping,
Stefan. Supporting parallel R
code in clinical trials: a grid-based approach. In Proc. of the 4th
IEEE ISPA 2008 Workshop on High Performance and Grid Computing in Medicine
and Biology (HiPGCoMB08), Sydney, Australia, December, 2008.
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Tsiknakis, Manolis, Sfakianakis, Stelios, Rüping, Stefan, Trelles,
Oswaldo, Sengstag, Thierry, Claerhout, Brecht, Virvilis,
Vassilis: A
Semantic Grid Services Architecture in Support of Efficient Knowledge
Discovery from Multilevel Clinical and Genomic Datasets. In:
Proceedings of the First International Conference on Health Informatics
(HEALTHINF), Funchal, Madeira, Portugal, 279-287, 2008.
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2007 |
Paaß, Gerhard, Reinhardt, Wolf, Rüping, Stefan, Wrobel, Stefan.
Data mining for security and crime detection.
In: Security informatics and terrorism: social and technical problems of
detecting and controlling terrorists' use of the World Wide Web ;
proceedings of the NATO Advanced Research Workshop on Security Informatics
and Terrorism - Patrolling the Web, Gal, Cecilia S. (Ed.). Beer-Sheva,
Israel, 4-5 June 2007. Amsterdam [u.a.]: IOS Press, 2008. (NATO ASI series
: Series D, Information and Communication Security 15), pp. 56-70
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Rendenbach, Hans-Georg und Rüping, Stefan. Controlling in dynamischem
Umfeld. Versicherungswirtschaft, 63. Jahrgang, Heft 11, 2008.
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Krause-Traudes, Maike, Scheider, Simon, Rüping, Stefan,
Meßner, Harald.
Spatial data mining for retail sales forecasting.
In: AGILE 2008 conference proceedings / CD-ROM: taking geoinformation
science one step further, Bernard, Lars (Ed.): . AGILE, 2008.
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Wegener, Dennis, and Sengstag, Thierry, and Sfakianakis, Stelios and
Rüping, and Assi, Anthony.
GridR: An R-based
grid-enabled tool for data analysis in ACGT clinico-genomic trials.
In: Proceedings of the 3rd International Conference on e-Science and Grid
Computing (eScience 2007), Bangalore, India, 2007.
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Rüping, Stefan, Sfakianakis, Stelios and Tsiknakis, Manolis.
Extending Workflow
Management for Knowledge Discovery in Clinico-Genomic Data.
In: From Genes to Personalized HealthCare: Grid Solutions for
the Life Sciences, Proceedings of HealthGrid 2007,
pp. 183-193,
IOS Press, 2007.
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Potamias, George, Koumakis, Lefteris, Kanterakis, Alexandros, Sfakianakis,
Stelios, Analyti, Anastasia, Moustakis, Vassilis, Kafetzopoulos, Dimitris,
Rüping, Stefan, Tsiknakis, Manolis:
Knowledge Discovery Scientific
Workflows in Clinico-Genomics. 19th IEEE International Conference on
Tools with Artificial Intelligence (ICTAI 2007), October 29-31, 2007,
Patras, Greece, 91-95, 2007.
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2006 |
Rüping, Stefan.
Learning Interpretable
Models. Ph.D. Thesis, Universität Dortmund, 2006.
URL: http://hdl.handle.net/2003/23008.
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May, Michael and Potamias, George and Rüping, Stefan.
Grid-based Knowledge Discovery in Clinico-Genomic Data.
In: Proceedings of the 7th International Symposium on Biological and
Medical Data Analysis (ISBMDA 2006), pp. 219-230,
Springer, 2006.
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Rüping, Stefan. Robust Probabilistic Calibration.
In: Proceedings of the European Conference on Machine Learning (ECML),
pp. 743-750, Springer, 2006.
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Morik, Katharina and Rüping, Stefan.
Klassifikations-/Clustermethoden und Konjunkturanalyse.
Duncker & Humbolt, 2006.
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≤2005 |
Rüping, Stefan.
Interpreting Classifiers by Multiple Views.
In: Proceedings of the ICML 2005 Workshop on Learning with Multiple Views,
2005.
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Rüping, Stefan.
Classification with Local Models.
In: Morik, K. and Boulicaut, J.-F. and Siebes, A. (editors), Proceedings of the
Dagstuhl Workshop on Detecting Local Patterns,
Springer, 2005.
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Rüping, Stefan and Scheffer, Tobias (editors).
Proceedings of the ICML 2005 Workshop on Learning with Multiple Views.
2005.
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Pumplün, Constanze and Rüping, Stefan and Morik, Katharina and
Weihs, Claus.
D-Optimal plans in observational studies.
Technical report 44/05, SFB475, University of Dortmund.
2005.
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Christmann, Andreas and Luebke, Karsten and Rüping, Stefan and
Marin-Galiano, Marcos.
Determination of
Hyper-Parameters for Kernel-based Classification and Regression.
Technical report 38/05, SFB475, University of Dortmund.
2005.
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Rüping, Stefan.
A Simple Method for Estimating
Conditional Probabilities in SVMs.
In: Abecker, A. and Bickel, S. and Brefeld, U. and Drost, I. and Henze,N. and Herden, O. and Minor, M. and Scheffer, T. and Stojanovic, L. and Weibelzahl, S. (editors),
LWA 2004 - Lernen - Wissensentdeckung - Adaptivität,
Humboldt-Universität Berlin, 2004.
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Klinkenberg, Ralf and Rüping, Stefan.
Concept Drift and the Importance of Examples.
In:
Franke, Jürgen and Nakhaeizadeh, Gholamreza and Renz, Ingrid (editors), Text Mining - Theoretical Aspects and Applications,
pp. 55-77,
Berlin, Germany,
Physica-Verlag,
2003.
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Rüping, Stefan and Morik, Katharina.
Support Vector Machines and Learning about Time.
In:
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'03),
2003.
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Morik, Katharina and Joachims, Thorsten and Imhoff, Michael and Brockhausen, Peter and Rüping, Stefan.
Integrating Kernel Methods
into a Knowledge-based Approach to Evidence-based Medicine.
In:
Schmitt, M. and Teodorescu, H. and Jain, A. and Jain, A. and Jain, S. and Jain, L. (editors),
Computational Intelligence Processing in Medical Diagnosis,
Vol. 96,
pp. 71-99,
Physica-Verlag,
2002.
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Morik, Katharina and Rüping, Stefan.
A Multistrategy Approach
to the Classification of Phases in Business Cycles.
In:
Elomaa, Taprio and Mannila, Heikki and Toivonen, Hannu (editors),
Machine Learning: ECML 2002,
Vol. 2430,
pp. 307-318,
Berlin,
Springer,
2002.
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Stefan Rüping.
Support Vector Machines in Relational Databases.
In:
Seong-Whan Lee and Alessandro Verri (editors),
Pattern Recognition with Support Vector Machines - First International Workshop, SVM 2002,
pp. 310-320,
Springer,
2002.
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Rüping, Stefan.
Efficient Kernel Calculation for Multirelational Data.
In:
Kokai, Gabriella and Zeidler, Jens (editors),
Proceedings der FGML 2002,
pp. 121-126,
Learning Lab Lower Saxony, Hannover, Germany,
2002.
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Klinkenberg, Ralf and Rüping, Stefan and Fick, Andreas and Henze, Nicola and Herzog, Christian and Molitor, Ralf and Schrüder, Olaf (editors).
LLWA 01 - Tagungsband der GI-Workshop-Woche Lernen - Lehren - Wissen - Adaptivität.
No. 763,
Dortmund, Germany,
2001.
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Rüping, Stefan.
SVM Kernels for Time Series Analysis.
In:
Klinkenberg, Ralf and Rüping, Stefan and Fick, Andreas and Henze, Nicola and Herzog, Christian and Molitor, Ralf and Schrüder, Olaf (editors),
LLWA 01 - Tagungsband der GI-Workshop-Woche Lernen - Lehren - Wissen - Adaptivität,
pp. 43-50,
Dortmund, Germany,
2001.
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Rüping, Stefan.
Incremental Learning with Support Vector Machines.
In:
Cercone, Nick and Lin, T.Y. and Wu, Xindong (editors),
Proceedings of the 2001 IEEE International Conference on Data Mining (ICDM '01),
pp. 641-642,
IEEE,
2001.
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Rüping, Stefan.
Zeitreihenprognose für Warenwirtschaftssysteme unter Berücksichtigung asymmetrischer Kostenfunktionen.
Universität Dortmund,
1999. In German.
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