| 2008 |
|---|
| 79 | EE | Marc Strickert,
Petra Schneider,
Jens Keilwagen,
Thomas Villmann,
Michael Biehl,
Barbara Hammer:
Discriminatory Data Mapping by Matrix-Based Supervised Learning Metrics.
ANNPR 2008: 78-89 |
| 78 | | Marc Strickert,
Nese Sreenivasulu,
Thomas Villmann,
Barbara Hammer:
Robust Centroid-Based Clustering using Derivatives of Pearson Correlation.
BIOSIGNALS (2) 2008: 197-203 |
| 77 | EE | Frank-Michael Schleif,
Matthias Ongyerth,
Thomas Villmann:
Sparse Coding Neural Gas for Analysis of Nuclear Magnetic Resonance Spectroscopy.
CBMS 2008: 620-625 |
| 76 | EE | Marc Strickert,
Frank-Michael Schleif,
Thomas Villmann:
Metric adaptation for supervised attribute rating.
ESANN 2008: 31-36 |
| 75 | EE | Alexander Hasenfuss,
Barbara Hammer,
Tina Geweniger,
Thomas Villmann:
Magnification Control in Relational Neural Gas.
ESANN 2008: 325-330 |
| 74 | EE | Thomas Villmann,
Erzsébet Merényi,
Udo Seiffert:
Machine learning approches and pattern recognition for spectral data.
ESANN 2008: 433-444 |
| 73 | EE | Petra Schneider,
Frank-Michael Schleif,
Thomas Villmann,
Michael Biehl:
Generalized matrix learning vector quantizer for the analysis of spectral data.
ESANN 2008: 451-456 |
| 72 | EE | Frank-Michael Schleif,
Thomas Villmann,
Barbara Hammer,
Martijn van der Werff,
André M. Deelder,
R. A. E. M. Tollenaar:
Analysis of Spectral Data in Clinical Proteomics by Use of Learning Vector Quantizers.
Computational Intelligence in Biomedicine and Bioinformatics 2008: 141-167 |
| 71 | EE | Thomas Villmann,
Frank-Michael Schleif,
Markus Kostrzewa,
Axel Walch,
Barbara Hammer:
Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods.
Briefings in Bioinformatics 9(2): 129-143 (2008) |
| 70 | EE | Frank-Michael Schleif,
Thomas Villmann,
Barbara Hammer:
Prototype based fuzzy classification in clinical proteomics.
Int. J. Approx. Reasoning 47(1): 4-16 (2008) |
| 2007 |
|---|
| 69 | | Michael Biehl,
Barbara Hammer,
Michel Verleysen,
Thomas Villmann:
Similarity-based Clustering and its Application to Medicine and Biology, 25.03. - 30.03.2007
Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany 2007 |
| 68 | EE | Thomas Villmann,
Marc Strickert,
Cornelia Brüß,
Frank-Michael Schleif,
Udo Seiffert:
Visualization of Fuzzy Information in Fuzzy-Classification for Image Segmentation using MDS.
ESANN 2007: 103-108 |
| 67 | EE | Barbara Hammer,
Thomas Villmann:
How to process uncertainty in machine learning?.
ESANN 2007: 79-90 |
| 66 | EE | Barbara Hammer,
Alexander Hasenfuss,
Frank-Michael Schleif,
Thomas Villmann,
Marc Strickert,
Udo Seiffert:
Intuitive Clustering of Biological Data.
IJCNN 2007: 1877-1882 |
| 65 | EE | Frank-Michael Schleif,
Thomas Villmann,
Barbara Hammer:
Supervised Neural Gas for Classification of Functional Data and Its Application to the Analysis of Clinical Proteom Spectra.
IWANN 2007: 1036-1044 |
| 64 | EE | Alexander Hasenfuss,
Barbara Hammer,
Frank-Michael Schleif,
Thomas Villmann:
Neural Gas Clustering for Dissimilarity Data with Continuous Prototypes.
IWANN 2007: 539-546 |
| 63 | EE | Thomas Villmann,
Frank-Michael Schleif,
Erzsébet Merényi,
Barbara Hammer:
Fuzzy Labeled Self-Organizing Map for Classification of Spectra.
IWANN 2007: 556-563 |
| 62 | EE | Michael Biehl,
Barbara Hammer,
Michel Verleysen,
Thomas Villmann:
07131 Abstracts Collection -- Similarity-based Clustering and its Application to Medicine and Biology.
Similarity-based Clustering and its Application to Medicine and Biology 2007 |
| 61 | EE | Michael Biehl,
Barbara Hammer,
Michel Verleysen,
Thomas Villmann:
07131 Summary -- Similarity-based Clustering and its Application to Medicine and Biology.
Similarity-based Clustering and its Application to Medicine and Biology 2007 |
| 60 | EE | Frank-Michael Schleif,
Thomas Villmann,
Barbara Hammer:
Analysis of Proteomic Spectral Data by Multi Resolution Analysis and Self-Organizing Maps.
WILF 2007: 563-570 |
| 59 | EE | Erzsébet Merényi,
Abha Jain,
Thomas Villmann:
Explicit Magnification Control of Self-Organizing Maps for "Forbidden" Data.
IEEE Transactions on Neural Networks 18(3): 786-797 (2007) |
| 58 | EE | Frank-Michael Schleif,
Barbara Hammer,
Thomas Villmann:
Margin-based active learning for LVQ networks.
Neurocomputing 70(7-9): 1215-1224 (2007) |
| 57 | EE | Barbara Hammer,
Alexander Hasenfuss,
Thomas Villmann:
Magnification control for batch neural gas.
Neurocomputing 70(7-9): 1225-1234 (2007) |
| 2006 |
|---|
| 56 | EE | Barbara Hammer,
Alexander Hasenfuss,
Frank-Michael Schleif,
Thomas Villmann:
Supervised Batch Neural Gas.
ANNPR 2006: 33-45 |
| 55 | EE | Thomas Villmann,
Udo Seiffert,
Frank-Michael Schleif,
Cornelia Brüß,
Tina Geweniger,
Barbara Hammer:
Fuzzy Labeled Self-Organizing Map with Label-Adjusted Prototypes.
ANNPR 2006: 46-56 |
| 54 | EE | Thomas Villmann,
Barbara Hammer,
Udo Seiffert:
Perspectives of Self-adapted Self-organizing Clustering in Organic Computing.
BioADIT 2006: 141-159 |
| 53 | EE | Frank-Michael Schleif,
Thomas Elssner,
Markus Kostrzewa,
Thomas Villmann,
Barbara Hammer:
Analysis and Visualization of Proteomic Data by Fuzzy Labeled Self-Organizing Maps.
CBMS 2006: 919-924 |
| 52 | EE | Udo Seiffert,
Barbara Hammer,
Samuel Kaski,
Thomas Villmann:
Neural networks and machine learning in bioinformatics - theory and applications.
ESANN 2006: 521-532 |
| 51 | EE | Frank-Michael Schleif,
Barbara Hammer,
Thomas Villmann:
Margin based Active Learning for LVQ Networks.
ESANN 2006: 539-544 |
| 50 | EE | Cornelia Brüß,
Felix Bollenbeck,
Frank-Michael Schleif,
Winfriede Weschke,
Thomas Villmann,
Udo Seiffert:
Fuzzy image segmentation with Fuzzy Labelled Neural Gas.
ESANN 2006: 563-568 |
| 49 | EE | Barbara Hammer,
Alexander Hasenfuss,
Thomas Villmann:
Magnification control for batch neural gas.
ESANN 2006: 7-12 |
| 48 | EE | Barbara Hammer,
Thomas Villmann,
Frank-Michael Schleif,
Cornelia Albani,
Wieland Hermann:
Learning Vector Quantization Classification with Local Relevance Determination for Medical Data.
ICAISC 2006: 603-612 |
| 47 | EE | Thomas Villmann,
Barbara Hammer,
Frank-Michael Schleif,
Tina Geweniger,
Tom Fischer,
Marie Cottrell:
Prototype Based Classification Using Information Theoretic Learning.
ICONIP (2) 2006: 40-49 |
| 46 | EE | Thomas Villmann,
Jens Christian Claussen:
Magnification Control in Self-Organizing Maps and Neural Gas.
Neural Computation 18(2): 446-469 (2006) |
| 45 | EE | Thomas Villmann,
Frank-Michael Schleif,
Barbara Hammer:
Comparison of relevance learning vector quantization with other metric adaptive classification methods.
Neural Networks 19(5): 610-622 (2006) |
| 44 | EE | Marie Cottrell,
Barbara Hammer,
Alexander Hasenfuss,
Thomas Villmann:
Batch and median neural gas.
Neural Networks 19(6-7): 762-771 (2006) |
| 43 | EE | Thomas Villmann,
Barbara Hammer,
Frank-Michael Schleif,
Tina Geweniger,
Wieland Hermann:
Fuzzy classification by fuzzy labeled neural gas.
Neural Networks 19(6-7): 772-779 (2006) |
| 42 | EE | Thomas Villmann,
Frank-Michael Schleif,
Barbara Hammer:
Prototype-based fuzzy classification with local relevance for proteomics.
Neurocomputing 69(16-18): 2425-2428 (2006) |
| 41 | EE | Marc Strickert,
Udo Seiffert,
Nese Sreenivasulu,
Winfriede Weschke,
Thomas Villmann,
Barbara Hammer:
Generalized relevance LVQ (GRLVQ) with correlation measures for gene expression analysis.
Neurocomputing 69(7-9): 651-659 (2006) |
| 2005 |
|---|
| 40 | EE | Barbara Hammer,
Andreas Rechtien,
Marc Strickert,
Thomas Villmann:
Relevance learning for mental disease classification.
ESANN 2005: 139-144 |
| 39 | EE | Barbara Hammer,
Thomas Villmann:
Classification using non-standard metrics.
ESANN 2005: 303-316 |
| 38 | EE | Marc Strickert,
Nese Sreenivasulu,
Winfriede Weschke,
Udo Seiffert,
Thomas Villmann:
Generalized Relevance LVQ with Correlation Measures for Biological Data.
ESANN 2005: 331-338 |
| 37 | EE | Frank-Michael Schleif,
Thomas Villmann,
Barbara Hammer:
Local Metric Adaptation for Soft Nearest Prototype Classification to Classify Proteomic Data.
WILF 2005: 290-296 |
| 36 | EE | Barbara Hammer,
Marc Strickert,
Thomas Villmann:
Supervised Neural Gas with General Similarity Measure.
Neural Processing Letters 21(1): 21-44 (2005) |
| 35 | EE | Barbara Hammer,
Marc Strickert,
Thomas Villmann:
On the Generalization Ability of GRLVQ Networks.
Neural Processing Letters 21(2): 109-120 (2005) |
| 34 | EE | Marie Cottrell,
Barbara Hammer,
Thomas Villmann:
New Aspects in Neurocomputing.
Neurocomputing 63: 1-3 (2005) |
| 33 | EE | Jens Christian Claussen,
Thomas Villmann:
Magnification control in winner relaxing neural gas.
Neurocomputing 63: 125-137 (2005) |
| 32 | EE | Jochen J. Steil,
Gavin C. Cawley,
Thomas Villmann:
Trends in Neurocomputing at ESANN 2004.
Neurocomputing 64: 1-4 (2005) |
| 2004 |
|---|
| 31 | EE | Thomas Villmann,
Udo Seiffert,
Axel Wismüller:
Theory and applications of neural maps.
ESANN 2004: 25-38 |
| 30 | EE | Barbara Hammer,
Marc Strickert,
Thomas Villmann:
Relevance LVQ versus SVM.
ICAISC 2004: 592-597 |
| 29 | EE | Thomas Villmann:
Special issue on new aspects in neurocomputing.
Neurocomputing 57: 1-2 (2004) |
| 28 | EE | Thomas Villmann,
Beate Villmann,
Volker Slowik:
Evolutionary algorithms with neighborhood cooperativeness according to neural maps.
Neurocomputing 57: 151-169 (2004) |
| 2003 |
|---|
| 27 | EE | Barbara Hammer,
Thomas Villmann:
Mathematical Aspects of Neural Networks.
ESANN 2003: 59-72 |
| 26 | EE | Jens Christian Claussen,
Thomas Villmann:
Magnification Control in Winner Relaxing Neural Gas.
ESANN 2003: 93-98 |
| 25 | EE | Thomas Villmann,
Erzsébet Merényi,
Barbara Hammer:
Neural maps in remote sensing image analysis.
Neural Networks 16(3-4): 389-403 (2003) |
| 2002 |
|---|
| 24 | | Axel Wismüller,
Thomas Villmann:
Exploratory Data Analysis in Medicine and Bioinformatics.
ESANN 2002: 25-38 |
| 23 | | Barbara Hammer,
Thomas Villmann:
Batch-RLVQ.
ESANN 2002: 295-300 |
| 22 | EE | Barbara Hammer,
Marc Strickert,
Thomas Villmann:
Learning Vector Quantization for Multimodal Data.
ICANN 2002: 370-376 |
| 21 | EE | Barbara Hammer,
Andreas Rechtien,
Marc Strickert,
Thomas Villmann:
Rule Extraction from Self-Organizing Networks.
ICANN 2002: 877-883 |
| 20 | EE | Jutta Huhse,
Thomas Villmann,
Peter Merz,
Andreas Zell:
Evolution Strategy with Neighborhood Attraction Using a Neural Gas Approach.
PPSN 2002: 391-400 |
| 19 | EE | Barbara Hammer,
Thomas Villmann:
Generalized relevance learning vector quantization.
Neural Networks 15(8-9): 1059-1068 (2002) |
| 18 | EE | Thomas Villmann:
Neural maps for faithful data modelling in medicine - state-of-the-art and exemplary applications.
Neurocomputing 48(1-4): 229-250 (2002) |
| 2001 |
|---|
| 17 | EE | Thomas Villmann:
Evolutionary algorithms and neural networks in hybrid systems.
ESANN 2001: 137-152 |
| 16 | EE | Barbara Hammer,
Thomas Villmann:
Input pruning for neural gas architectures.
ESANN 2001: 283-288 |
| 15 | EE | Thomas Villmann,
Conny Albani:
Clustering of Categoric Data in Medicine - Application of Evolutionary Algorithms.
Fuzzy Days 2001: 619-627 |
| 2000 |
|---|
| 14 | EE | Thomas Villmann:
Neural networks approaches in medicine - a review of actual developments.
ESANN 2000: 165-176 |
| 13 | EE | Thomas Villmann,
R. Haupt,
Klaus Hering:
Parallel Evolutionary Algorithms with SOM-Like Migration and its Application to VLSI-Design.
IJCNN (5) 2000: 167-172 |
| 12 | EE | Thomas Villmann,
Wieland Hermann,
Michael Geyer:
Data Mining and Knowledge Discovery in Medical Applications Using Self-Organizing Maps.
ISMDA 2000: 138-151 |
| 1999 |
|---|
| 11 | EE | Thomas Villmann:
Benefits and limits of the self-organizing map and its variants in the area of satellite remote sensoring processing.
ESANN 1999: 111-116 |
| 10 | EE | Hans-Ulrich Bauer,
J. Michael Herrmann,
Thomas Villmann:
Neural maps and topographic vector quantization.
Neural Networks 12(4-5): 659-676 (1999) |
| 1998 |
|---|
| 9 | EE | Thomas Villmann,
J. Michael Herrmann:
Magnification control in neural maps.
ESANN 1998: 191-196 |
| 8 | | Thomas Villmann,
A. Körner,
Conny Albani:
Evolutionary Algorithms with Self-Organizing Population Dynamic for Clustering of Categories in Psychotherapy Research Using Large Clinical Data Sets.
NC 1998: 130-136 |
| 7 | EE | Thomas Villmann,
Hans-Ulrich Bauer:
Applications of the growing self-organizing map.
Neurocomputing 21(1-3): 91-100 (1998) |
| 1997 |
|---|
| 6 | | J. Michael Herrmann,
Hans-Ulrich Bauer,
Thomas Villmann:
Measuring topology preservation in maps of real-world data.
ESANN 1997 |
| 5 | | Thomas Villmann,
Beate Villmann,
Conny Albani:
Application of Evolutionary Algorithms to the Problem of New Clustering of Psychological Categories Using Real Clinical Data Sets.
Fuzzy Days 1997: 311-320 |
| 4 | | J. Michael Herrmann,
Thomas Villmann:
Vector Quantization by Optimal Neural Gas.
ICANN 1997: 625-630 |
| 1996 |
|---|
| 3 | EE | Klaus Hering,
R. Haupt,
Thomas Villmann:
Hierarchical Strategy of Model Partitioning for VLSI-Design Using an Improved Mixture of Experts Approach.
Workshop on Parallel and Distributed Simulation 1996: 106-113 |
| 1994 |
|---|
| 2 | | Thomas Villmann,
Ralf Der,
J. Michael Herrmann,
Thomas Martinetz:
Topology Preservation in Self-Organizing Feature Maps: General Definition and Efficient Measurement.
Fuzzy Days 1994: 159-166 |
| 1993 |
|---|
| 1 | | Ralf Der,
Thomas Villmann:
Dynamics of Self-Organized Feature Mapping.
IWANN 1993: 312-315 |
