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| , and , Fuzzy Learning Vector Quantization with Size and Shape Parameters, in: Proc. 15th IEEE Int. Conf. on Fuzzy Systems, 2005 (FUZZ-IEEE'05, Reno, NV), CD-ROM, pages 195--200, IEEE Press, 2005 |
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| , and , Graphical Models: Representations for Learning, Reasoning and Data Mining, Wiley, 2009 |
| , and , Using Fuzzy Clustering to Improve Naive Bayes Classifiers and Probabilistic Networks, in: Proc.\ 9th IEEE Int.\ Conf.\ on Fuzzy Systems (FUZZ-IEEE'00, San Antonio, TX), IEEE Press, 2000 |
| , and , Unsicheres und vages Wissen, in: Einführung in die Künstliche Intelligenz (3.~Auflage), pages 291--347, Addison-Wesley, 2000 |
| , and , Probabilistic Networks and Fuzzy Clustering as Generalizations of Naive Bayes Classifiers, in: Computational Intelligence in Theory and Practice, pages 121--138, Physica-Verlag, 2001 |
| , , , , , , and , Network Farthest-Point Diagrams (2013), in: arXiv preprint arXiv:1304.1909 |
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| , Optimierung numerischer Eingabeparameter für eine Flughafenschnellzeitsimulation, Faculty of Computer Science, University of Magdeburg, 2012 |
| , Contrast and change mining (2011), in: Wiley Interdisc. Rev.: Data Mining and Knowledge Discovery, 1:3(215-230) |
| , Discovering Interesting Temporal Changes in Association Rules, Otto-von-Guericke-Universität Magdeburg, 2005 |
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| , and , On exploiting the power of time in data mining (2008), in: SIGKDD Explorations, 10:2(3-11) |
| , , and , A Framework for Discovering Interesting Business Changes from Data (2006), in: BT Technology Journal, 24:2(219--228) |
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| , , and , From Change Mining to Relevance Feedback: A Unified View on Assessing Rule Interestingness, in: Post-Mining of Association Rules: Techniques for Effective Knowledge Extraction, pages 12-37, IGI Global, 2009 |
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| , and , A Condensed Representation of Itemsets for Analyzing their Evolution over Time, in: 11th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD2009), Springer, 2009 |
| , and , Predicting Future Decision Trees from Evolving Data, in: Proceedings of ICDM '08, Pisa, Italy, pages 33--42, IEEE Computer Society, 2008 |
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| , and , A temporal extension of closed item sets for change mining, School of Computer Science, University of Magdeburg, number 07-08, 2008 |
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| , and , An Algorithm for Anticipating Future Decision Trees from Concept-Drifting Data, in: Research and Development in Intelligent Systems, BCS SGAI, London, pages 293--306, Springer, 2009 |
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| , , and , Mining changing customer segments in dynamic markets (2009), in: Expert Systems with Applications, 36:1(155--164) |
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| Advances in Intelligent Data Analysis V, Springer, 2003 |
| , Analysis of Parallel Spike Trains with Clustering Methods, Otto von Guericke University Magdeburg, School of Computer Science, Department of Knowledge and Language Processing, 2012 |
| , Identifying Neuron Ensembles in Parallel Spike Trains: Detection Methods and Reduction of False-Positives, Otto-von-Guericke-Universität, 2011 |
| , and , Using Changes in Distribution to Identify Synchronized Point Processes, in: Strengthening Links Between Data Analysis and Soft Computing, pages 241-248, Springer International Publishing, 2015 |
| , and , Finding Ensembles of Neurons in Spike Trains by Non-linear Mapping and Statistical Testing, in: Advances in Intelligent Data Analysis X, pages 55-66, Springer Berlin / Heidelberg, 2011 |
| , and , Assembly Detection in Continuous Neural Spike Train Data, in: Advances in Intelligent Data Analysis XI, pages 78-89, Springer Berlin / Heidelberg, 2012 |
| , and , Behavioral Clustering for Point Processes, in: Advances in Intelligent Data Analysis XII, pages 127-137, Springer Berlin Heidelberg, 2013 |
| , and , Obtaining shape descriptors from a concave hull-based clustering algorithm, in: Advances in Intelligent Data Analysis XV : 15th International Symposium, IDA 2016, Stockholm, Sweden, October 13-15, 2016, Proceedings, Stockholm, Sweden, pages 61-72, 2016 |
| , and , Towards Online Detection of Neural Assemblies in Parallel Spike Trains, in: 48th Hawaii International Conference on System Sciences (HICSS), 2015, pages 1503-1511, 2015 |
| and , Fuzzy density based clustering with generalized centroids, in: 2016 IEEE Symposium Series on Computational Intelligence (SSCI), pages 1-7, 2016 |
| and , Detecting parallel bursts in in silico generated parallel spike train data, in: 24th Annual Computational Neuroscience Meeting: CNS*2015, pages P134, 2015 |
| and , Active Learning-Based Identification of Neuronal Assemblies in Parallel Spike Trains, in: Proceedings. 24. Workshop Computational Intelligence, Dortmund, 27.-28. November 2014, pages 155-172, KIT Scientific Publishing, 2014 |
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| , and , Axiomatic Treatment of Possibilistic Independence, in: Symbolic and Quantitative Approaches to Reasoning and Uncertainty, Lecture Notes in Artificial Intelligence 946, pages 77--88, Springer, 1995 |