Barbara Hammer

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Thomas VillmannProfessor for Mathematics and Computational Intelligence, University of Applied Sciences MittweidaVerified email at hs-mittweida.de
Frank-Michael SchleifProfessor of Computational Intelligence, Technical-UAS Würzburg-SchweinfurtVerified email at fhws.de
Michael BiehlUniversity of Groningen, Bernoulli InstituteVerified email at rug.nl
Bassam MokbelCITEC, Bielefeld UniversityVerified email at techfak.uni-bielefeld.de
Alexander SchulzTechnical Faculty, CITEC, Bielefeld UniversityVerified email at techfak.uni-bielefeld.de
Heiko WersingHonda Research Institute EuropeVerified email at honda-ri.de
Benjamin PaassenBielefeld UniversityVerified email at techfak.uni-bielefeld.de
Xibin ZhuCITEC, Center of Excellence, Bielefeld University, GermanyVerified email at techfak.uni-bielefeld.de
Kerstin BunteRosalind Franklin Fellow at the University of GroningenVerified email at rug.nl
Viktor LosingHonda Research Institute EuropeVerified email at honda-ri.de
Alessandro SperdutiUniversity of PadovaVerified email at math.unipd.it
Alessio MicheliDepartment of Computer Science, University of PisaVerified email at di.unipi.it
Niels PinkwartHumboldt-Universität zu Berlin & DFKIVerified email at informatik.hu-berlin.de
Christina GöpfertAssistant Researcher at Bielefeld UniversityVerified email at techfak.uni-bielefeld.de
Jan Philip GöpfertBielefeld UniversityVerified email at uni-bielefeld.de
Peter TinoProfessor of Complex and Adaptive Systems, University of Birmingham, UKVerified email at cs.bham.ac.uk
Babak HosseiniPostdoctoral Researcher in Pattern Recognition in Embedded Systems, TU DortmundVerified email at techfak.uni-bielefeld.de
marie cottrellSAMM Université Paris 1 Panthéon-SorbonneVerified email at univ-paris1.fr
David NebelCI Group MittweidaVerified email at hs-mittweida.de
Pascal HitzlerLloyd T. Smith Creativity in Engineering Chair, Kansas State University, Manhattan, KansasVerified email at ksu.edu

Barbara Hammer

Professor, Bielefeld University

Verified email at techfak.uni-bielefeld.de

machine learning data mining neural networks bioinformatics theoretical computer science


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Generalized relevance learning vector quantization B Hammer, T Villmann Neural Networks 15 (8-9), 1059-1068, 2002	550	2002
Adaptive relevance matrices in learning vector quantization P Schneider, M Biehl, B Hammer Neural computation 21 (12), 3532-3561, 2009	419	2009
Incremental learning algorithms and applications A Geppert, B Hammer ESANN, 2016	349	2016
Incremental on-line learning: A review and comparison of state of the art algorithms V Losing, B Hammer, H Wersing Neurocomputing 275, 1261-1274, 2018	303	2018
Neural maps in remote sensing image analysis T Villmann, E Merényi, B Hammer Neural Networks 16 (3-4), 389-403, 2003	233	2003
Parametric nonlinear dimensionality reduction using kernel t-SNE A Gisbrecht, A Schulz, B Hammer Neurocomputing 147, 71-82, 2015	223	2015
KNN Classifier with Self Adjusting Memory for Heterogeneous Concept Drift V Losing, B Hammer, H Wersing IEEE International Conference on Data Mining (ICDM), 2016	218	2016
Supervised neural gas with general similarity measure B Hammer, M Strickert, T Villmann Neural Processing Letters 21, 21-44, 2005	183	2005
Batch and median neural gas M Cottrell, B Hammer, A Hasenfuß, T Villmann Neural Networks 19 (6-7), 762-771, 2006	179	2006
Merge SOM for temporal data M Strickert, B Hammer Neurocomputing 64, 39-71, 2005	174	2005
Recursive self-organizing network models B Hammer, A Micheli, A Sperduti, M Strickert Neural Networks 17 (8-9), 1061-1085, 2004	165	2004
On the approximation capability of recurrent neural networks B Hammer Neurocomputing 31 (1-4), 107-123, 2000	161	2000
A note on the universal approximation capability of support vector machines B Hammer, K Gersmann neural processing letters 17, 43-53, 2003	144	2003
Prototype‐based models in machine learning M Biehl, B Hammer, T Villmann Wiley Interdisciplinary Reviews: Cognitive Science 7 (2), 92-111, 2016	141	2016
Limited rank matrix learning, discriminative dimension reduction and visualization K Bunte, P Schneider, B Hammer, FM Schleif, T Villmann, M Biehl Neural Networks 26, 159-173, 2012	136	2012
Distance learning in discriminative vector quantization P Schneider, M Biehl, B Hammer Neural computation 21 (10), 2942-2969, 2009	135	2009
Dynamics and Generalization Ability of LVQ Algorithms. M Biehl, A Ghosh, B Hammer Journal of Machine Learning Research 8 (2), 2007	133	2007
A general framework for unsupervised processing of structured data B Hammer, A Micheli, A Sperduti, M Strickert Neurocomputing 57, 3-35, 2004	127	2004
A general framework for dimensionality-reducing data visualization mapping K Bunte, M Biehl, B Hammer Neural Computation 24 (3), 771-804, 2012	124	2012
Topographic mapping of large dissimilarity data sets B Hammer, A Hasenfuss Neural Computation 22 (9), 2229-2284, 2010	118	2010

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