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 | 149 | 2012 |
Reactive soft prototype computing for concept drift streams C Raab, M Heusinger, FM Schleif Neurocomputing 416, 340-351, 2020 | 123 | 2020 |
Indefinite proximity learning: A review FM Schleif, P Tino Neural computation 27 (10), 2039-2096, 2015 | 105 | 2015 |
Learning vector quantization for (dis-) similarities B Hammer, D Hofmann, FM Schleif, X Zhu Neurocomputing 131, 43-51, 2014 | 87 | 2014 |
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 | 76 | 2011 |
Metric and non-metric proximity transformations at linear costs A Gisbrecht, FM Schleif Neurocomputing 167, 643-657, 2015 | 56 | 2015 |
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 | 56 | 2008 |
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 | 52 | 2006 |
Efficient kernelized prototype based classification FM Schleif, T Villmann, B Hammer, P Schneider International journal of neural systems 21 (06), 443-457, 2011 | 44 | 2011 |
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 | 39 | 2006 |
Metric learning for sequences in relational LVQ B Mokbel, B Paassen, FM Schleif, B Hammer Neurocomputing 169, 306-322, 2015 | 37 | 2015 |
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 | 34 | 2015 |
Margin-based active learning for LVQ networks FM Schleif, B Hammer, T Villmann Neurocomputing 70 (7-9), 1215-1224, 2007 | 34 | 2007 |
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 | 32 | 2016 |
Prototype based fuzzy classification in clinical proteomics FM Schleif, T Villmann, B Hammer International Journal of Approximate Reasoning 47 (1), 4-16, 2008 | 30 | 2008 |
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 | 28 | 2009 |
Indefinite core vector machine FM Schleif, P Tino Pattern Recognition 71, 187-195, 2017 | 27 | 2017 |
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 | 27 | 2012 |
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 | 26 | 2009 |
Learning interpretable kernelized prototype-based models D Hofmann, FM Schleif, B Paaßen, B Hammer Neurocomputing 141, 84-96, 2014 | 25 | 2014 |