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Frank-Michael Schleif
Frank-Michael Schleif
Professor of Computational Intelligence, Technical-UAS Würzburg-Schweinfurt
Bestätigte E-Mail-Adresse bei thws.de - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Reactive soft prototype computing for concept drift streams
C Raab, M Heusinger, FM Schleif
Neurocomputing 416, 340-351, 2020
1772020
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
1532012
Indefinite proximity learning: A review
FM Schleif, P Tino
Neural computation 27 (10), 2039-2096, 2015
1122015
Learning vector quantization for (dis-) similarities
B Hammer, D Hofmann, FM Schleif, X Zhu
Neurocomputing 131, 43-51, 2014
882014
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
772011
Metric and non-metric proximity transformations at linear costs
A Gisbrecht, FM Schleif
Neurocomputing 167, 643-657, 2015
612015
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
582008
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
522006
Efficient kernelized prototype based classification
FM Schleif, T Villmann, B Hammer, P Schneider
International journal of neural systems 21 (06), 443-457, 2011
442011
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
392006
Stationarity of matrix relevance LVQ
M Biehl, B Hammer, FM Schleif, P Schneider, T Villmann
2015 International Joint Conference on Neural Networks (IJCNN), 1-8, 2015
382015
Metric learning for sequences in relational LVQ
B Mokbel, B Paassen, FM Schleif, B Hammer
Neurocomputing 169, 306-322, 2015
372015
Margin-based active learning for LVQ networks
FM Schleif, B Hammer, T Villmann
Neurocomputing 70 (7-9), 1215-1224, 2007
342007
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, 207-220, 2016
332016
Prototype based fuzzy classification in clinical proteomics
FM Schleif, T Villmann, B Hammer
International Journal of Approximate Reasoning 47 (1), 4-16, 2008
312008
Indefinite core vector machine
FM Schleif, P Tino
Pattern Recognition 71, 187-195, 2017
282017
Learning interpretable kernelized prototype-based models
D Hofmann, FM Schleif, B Paaßen, B Hammer
Neurocomputing 141, 84-96, 2014
272014
Large margin linear discriminative visualization by matrix relevance learning
M Biehl, K Bunte, FM Schleif, P Schneider, T Villmann
The 2012 International Joint Conference on Neural Networks (IJCNN), 1-8, 2012
272012
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, 189-199, 2009
272009
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
272009
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