Frank-Michael Schleif
Frank-Michael Schleif
Professor of Database Management and Business Intelligence, University of Applied Sciences Würzburg
Verified email at fhws.de - Homepage
TitleCited byYear
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
922012
Learning vector quantization for (dis-) similarities
B Hammer, D Hofmann, FM Schleif, X Zhu
Neurocomputing 131, 43-51, 2014
652014
Divergence-based classification in learning vector quantization
E Mwebaze, P Schneider, FM Schleif, JR Aduwo, JA Quinn, S Haase, ...
Neurocomputing 74 (9), 1429-1435, 2011
502011
Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods
T Villmann, FM Schleif, M Kostrzewa, A Walch, B Hammer
Briefings in Bioinformatics 9 (2), 129-143, 2008
502008
Indefinite proximity learning: A review
FM Schleif, P Tino
Neural computation 27 (10), 2039-2096, 2015
492015
Fuzzy classification by fuzzy labeled neural gas
T Villmann, B Hammer, F Schleif, T Geweniger, W Herrmann
Neural Networks 19 (6-7), 772-779, 2006
442006
Comparison of relevance learning vector quantization with other metric adaptive classification methods
T Villmann, F Schleif, B Hammer
Neural Networks 19 (5), 610-622, 2006
362006
Efficient kernelized prototype based classification
FM Schleif, T Villmann, B Hammer, P Schneider
International journal of neural systems 21 (06), 443-457, 2011
342011
Metric and non-metric proximity transformations at linear costs
A Gisbrecht, FM Schleif
Neurocomputing 167, 643-657, 2015
282015
Margin-based active learning for LVQ networks
FM Schleif, B Hammer, T Villmann
Neurocomputing 70 (7-9), 1215-1224, 2007
282007
Support vector classification of proteomic profile spectra based on feature extraction with the bi-orthogonal discrete wavelet transform
FM Schleif, M Lindemann, M Diaz, P Maaß, J Decker, T Elssner, M Kuhn, ...
Computing and visualization in science 12 (4), 189-199, 2009
252009
Cancer informatics by prototype networks in mass spectrometry
FM Schleif, T Villmann, M Kostrzewa, B Hammer, A Gammerman
Artificial Intelligence in Medicine 45 (2-3), 215-228, 2009
252009
Linear time relational prototype based learning
A Gisbrecht, B Mokbel, FM Schleif, X Zhu, B Hammer
International journal of neural systems 22 (05), 1250021, 2012
242012
Prototype based fuzzy classification in clinical proteomics
FM Schleif, T Villmann, B Hammer
International Journal of Approximate Reasoning 47 (1), 4-16, 2008
242008
Metric learning for sequences in relational LVQ
B Mokbel, B Paassen, FM Schleif, B Hammer
Neurocomputing 169, 306-322, 2015
232015
Supervised batch neural gas
B Hammer, A Hasenfuss, FM Schleif, T Villmann
IAPR Workshop on Artificial Neural Networks in Pattern Recognition, 33-45, 2006
232006
Odor recognition in robotics applications by discriminative time-series modeling
FM Schleif, B Hammer, JG Monroy, JG Jimenez, JL Blanco-Claraco, ...
Pattern Analysis and Applications 19 (1), 207-220, 2016
222016
Data analysis of (non-) metric proximities at linear costs
FM Schleif, A Gisbrecht
International Workshop on Similarity-Based Pattern Recognition, 59-74, 2013
222013
Supervised neural gas and relevance learning in learning vector quantization
T Villmann, FM Schleif, B Hammer
Proceedings of the workshop on Self-organizing Maps (WSOM), Japan, 2003
222003
Learning interpretable kernelized prototype-based models
D Hofmann, FM Schleif, B Paassen, B Hammer
Neurocomputing 141, 84-96, 2014
202014
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