All publications sorted by title
L
Christian Borgelt and Rudolf Kruse, Learning from Imprecise Data: Possibilistic Graphical Models, in: Proc.\ Int.\ Meeting on Nonlinear Methods and Data Mining (NMDM 2000), pages 190--203, Consiglio Nazionale delle Ricerche, 2000
Christian Borgelt and Rudolf Kruse, Learning Graphical Models by Extending Optimal Spanning Trees, in: Intelligent Systems for Information Processing --- From Representation to Applications, pages 339--348, Elsevier, 2003
Christian Borgelt and Rudolf Kruse, Learning Graphical Models with Hypertree Structure Using a Simulated Annealing Approach, in: Proc.\ 10th IEEE Int.\ Conf.\ on Fuzzy Systems (FUZZ-IEEE'01, Melbourne, Australia), IEEE Press, 2001
Detlef Nauck and Rudolf Kruse, Learning in Neuro-Fuzzy Systems with Symbolic Attributes and Missing Values, in: Proc. Sixth International Conference on Information Processing (ICONIP99), pages 142--147, Perth, 1999
Andreas Nürnberger and Rudolf Kruse, Learning methods for fuzzy systems, in: Proc. 8th International Symposium on Non-Linear Electromagnetic Systems 1997 (ISEM'97), 1997
Andreas Nürnberger and Rudolf Kruse, Learning Methods for Fuzzy Systems, in: Proc. of the 8th International Symposium on Non-Linear Electromagnetic Systems 1997 (ISEM'97), pages 367--372, IOS-Press, 1998 attachment
Rudolf Kruse and Detlef Nauck, Learning Methods for Fuzzy Systems, in: Proc.\ Fuzzy--Neuro--Systeme'95, pages 7--22, 1995
Tran Tuan Nguyen, Jens Spehr, Matthias Uhlemann, Sebastian Zug and Rudolf Kruse, Learning of lane information reliability for intelligent vehicles, in: 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), pages 142-147, 2016
Jörg Gebhardt and Rudolf Kruse, Learning Possibilistic Graphical Models, in: Proc. 3rd European Congress on Fuzzy and Intelligent Technologies (EUFIT'95), pages 74--76, 1995
Christian Borgelt, Guido Lindner and Rudolf Kruse, Learning Possibilistic Graphical Models from Data (2003), in: IEEE Transaction Fuzzy Systems, 11:2(159--172)
Jörg Gebhardt and Rudolf Kruse, Learning Possibilistic Networks from Data, pages 143--153, Springer, Learning from Data, Artificial Intelligence and Statistics 5, Le, volume 112, 1996
Jörg Gebhardt and Rudolf Kruse, Learning Possibilistic Networks from Data, in: Proc. 5th International Workshop on Artificial Intelligence and Statistics, pages 233--244, 1995
Jörg Gebhardt and Rudolf Kruse, Learning Possibilistic Networks from Data, in: Proceedings of FUZZ-IEEE / IFES '95, pages 1575--1580, 1995
Christian Borgelt and Rudolf Kruse, Learning probabilistic and possibilistic networks: Theory and applications, in: Proc. 7th International Fuzzy Systems Association World Congress (IFSA'97), pages 19--24, 1997
Sebastian Nusser, Clemens Otte, Werner Hauptmann and Rudolf Kruse, Learning Verifiable Ensembles for Classification Problems with High Safety Requirements, in: Intelligent Soft Computation and Evolving Data Mining: Integrating Advanced Technology, IGI Global, 2009
Christian Borgelt and Rudolf Kruse, Local Structure Learning in Graphical Models, in: Planning based on Decision Theory (Proc.\ 6th Int.\ Workshop, Udine, Italy 2002), pages 99--118, Springer-Verlag, 2003
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Roland Winkler, Frank Klawonn and Rudolf Kruse, M-Estimator induced Fuzzy Clustering Algorithms, in: Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-2011) and LFA-2011, European Society for Fuzzy Logic and Technology (EUSFLAT), Aix-Le-Bains, France, pages 298--304, Atlantis Press, 2011 attachment
Georg Ruß and Rudolf Kruse, Machine Learning Methods for Spatial Clustering on Precision Agriculture Data, in: Eleventh Scandinavian Conference on Artificial Intelligence, pages 40--49, IOS Press, 2011 attachment
Kristian Löwe, Mapping of WDLPS neochromosomes, Otto-von-Guericke-Universität Magdeburg, 2010 attachment
Rudolf Kruse and Frank Klawonn, Mass Distributions on L-Fuzzy Sets and Families of Frames of Discernment, pages 239--250, Wiley, Advances in Dempster-ShaferTheory of Evidence, 1994
Frank Rehm, Frank Klawonn and Rudolf Kruse, Mdspolar: A new approach for dimension reduction to visualize high dimensional data, in: Advances inIntelligent Data Analysis VI - Proc. of the 6th Int. Symp. on IDA 2005, Berlin, Heidelberg, pages 316--327, Springer, 2005
Jörg Gebhardt and Rudolf Kruse, Measures of Nonspecificity for Decomposing Possibility Distributions, in: Proc. Biennial Conference of the North American Fuzzy Information Processing Society (NAFIPS '96), pages 177--179, 1996
Kristian Löwe, Sarah E. Donohue, Mircea Ariel Schönfeld, Rudolf Kruse and Christian Borgelt, Memory-efficient analysis of dense functional connectomes (2016), in: Frontiers in neuroinformatics Lausanne Frontiers Research Foundation, 10 2016 12 Bd. 10.2016, Art.-Nr. 50, insges. 12 S.
Dominic Stange, Mining Associations Between Subsequences in Time-Series, Otto-von-Guericke-Universit{\"a}t Magdeburg, 2011 attachment
Mirko Böttcher, Martin Spott, Detlef Nauck and Rudolf Kruse, Mining changing customer segments in dynamic markets (2009), in: Expert Systems with Applications, 36:1(155--164) attachment
Rudolf Kruse, Christian Borgelt, Christian Braune and Kristian Löwe, Mining Frequent Parallel Episodes with Selective Participation, in: 16th World Congress of the International Fuzzy Systems Association (IFSA) 9th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), Atlantis Press, 2015
Steffen Kempe, Jochen Hipp, Carsten Lanquillon and Rudolf Kruse, Mining frequent temporal patterns in interval sequences (2008), in: International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (IJUFKS), 16:5(645--661) attachment
Xiaomeng Wang, Christian Borgelt and Rudolf Kruse, Mining Fuzzy Frequent Item Sets, in: Proc.\ 11th Int.\ Fuzzy Systems Association World Congress (IFSA'05, Beijing, China), pages 528--533, Tsinghua University Press and Springer-Verlag, 2005 attachment
Kristian Löwe, M. Grueschow and Christian Borgelt, Mining Local Connectivity Patterns in fMRI Data., in: Towards Advanced Data Analysis by Combining Soft Computing and Statistics, pages 305--317, Springer Berlin Heidelberg, 2013
Steffen Kempe and Jochen Hipp, Mining Sequences of Temporal Intervals, in: Knowledge Discovery in Databases: PKDD 2006, pages 569-576, Springer, 2006 attachment