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Frank-Michael Schleif

Observed names: F. -M. Schleif, F. Schleif, F.-M. SCHLEIF, F.-M. Schleif, FRANK-MICHAEL SCHLEIF, Frank-M. Schleif, Schleif, Frank Michael, Schleif, Frank-Michael
Observed institutions: Hochschule Mittweida, Bielefeld University, University of Würzburg, Technical University of Applied Sciences Würzburg-Schweinfurt, Bruker (Germany), Clausthal University of Technology, Statistique, Analyse et Modélisation Multidisciplinaire, University of Birmingham, Leipzig University, UCLouvain
ORCID: 0000-0002-7539-1283
Observed ORCID: 0000-0002-7539-1283
OpenAlex ID: A5004196006
Reactive Soft Prototype Computing for Concept Drift Streams
2020 · Christoph Raab, Moritz Heusinger, et al. · Neurocomputing · 182
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Limited Rank Matrix Learning, discriminative dimension reduction and visualization
2011 · Kerstin Bunte, Petra Schneider, et al. · Neural Networks · 108
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Indefinite Proximity Learning: A Review
2015 · Frank-Michael Schleif, Peter Tino · Neural Computation · 84
Learning vector quantization for (dis-)similarities
2013 · Barbara Hammer, Daniela Hofmann, et al. · Neurocomputing · 63
Divergence-based classification in learning vector quantization
2011 · E. Mwebaze, P. Schneider, et al. · Neurocomputing · 55
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Metric and non-metric proximity transformations at linear costs
2015 · Andrej Gisbrecht, Frank-Michael Schleif · Neurocomputing · 49
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Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods
2007 · T. Villmann, F.-M. Schleif, et al. · Briefings in Bioinformatics · 49
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Fuzzy classification by fuzzy labeled neural gas
2006 · Th. Villmann, B. Hammer, et al. · Neural Networks · 41
Proc. European Symposium on Artificial Neural Networks
2007 · Petra Schneider, Frank-Michael Schleif, et al. · 33
Efficient Kernelized Prototype Based Classification
2011 · F.-M. SCHLEIF, THOMAS VILLMANN, et al. · International Journal of Neural Systems · 32
Metric learning for sequences in relational LVQ
2015 · Bassam Mokbel, Benjamin Paassen, et al. · Neurocomputing · 31
Stationarity of Matrix Relevance LVQ
2015 · Michael Biehl, Barbara Hammer, et al. · International Joint Conference on Neural Networks (IJCNN) · 28
Margin-based active learning for LVQ networks
2006 · F.-M. Schleif, B. Hammer, et al. · Neurocomputing · 28
Comparison of relevance learning vector quantization with other metric adaptive classification methods
2005 · Th. Villmann, F. Schleif, et al. · Neural Networks · 28
Odor recognition in robotics applications by discriminative time-series modeling
2015 · Frank-Michael Schleif, Barbara Hammer, et al. · Pattern Analysis and Applications · 27
Indefinite Core Vector Machine
2017 · Frank-Michael Schleif, Peter Tino · Pattern Recognition · 26
Learning interpretable kernelized prototype-based models
2014 · Daniela Hofmann, Frank-Michael Schleif, et al. · Neurocomputing · 23
Data Analysis of (Non-)Metric Proximities at Linear Costs
2013 · Frank-Michael Schleif, Andrej Gisbrecht · Lecture notes in computer science · 23
Linear Time Relational Prototype Based Learning
2012 · ANDREJ GISBRECHT, BASSAM MOKBEL, et al. · International Journal of Neural Systems · 23
Derivatives of Pearson Correlation for Gradient-based Analysis of Biomedical Data
2008 · M. Strickert, F.-M. Schleif, et al. · INTELIGENCIA ARTIFICIAL · 21
Support vector classification of proteomic profile spectra based on feature extraction with the bi-orthogonal discrete wavelet transform
2008 · Frank-Michael Schleif, Mathias Lindemann, et al. · Computing and Visualization in Science · 21
Prototype based fuzzy classification in clinical proteomics
2007 · F.-M. Schleif, T. Villmann, et al. · International Journal of Approximate Reasoning · 21
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Cancer informatics by prototype networks in mass spectrometry
2008 · Frank-Michael Schleif, Thomas Villmann, et al. · Artificial Intelligence in Medicine · 20
Passive concept drift handling via variations of learning vector quantization
2020 · Moritz Heusinger, Christoph Raab, et al. · Neural Computing and Applications · 19
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Large margin linear discriminative visualization by Matrix Relevance Learning
2012 · Michael Biehl, Kerstin Bunte, et al. · International Joint Conference on Neural Networks (IJCNN) · 19
Works count: 230
Citation count: 1,952
H-index: 21
I10-index: 58
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