Thomas Villmann
91 publications
6 venues
H Index 19
Affiliation
University of Applied Sciences Mittweida, GermanyLinks
| Name | Venue | Year | citations |
|---|---|---|---|
A Robust Prototype-Based Network with Interpretable RBF Classifier Foundations.
|
AAAI | 2025 | 0 |
| About Vector Quantization and its Privacy in Federated Learning.
|
ESANN | 2024 | 1 |
| Domain Knowledge Integration in Machine Learning Systems - An Introduction.
|
ESANN | 2024 | 1 |
| Sparse Nyström Approximation for Non-Vectorial Data Using Class-informed Landmark Selection.
|
ESANN | 2023 | 0 |
| Variants of Neural Gas for Regression Learning.
|
ESANN | 2023 | 3 |
| Quantum Artificial Intelligence: A tutorial.
|
ESANN | 2023 | 1 |
| Quantum-ready vector quantization: Prototype learning as a binary optimization problem.
|
ESANN | 2023 | 3 |
| Learning Vector Quantization in Context of Information Bottleneck Theory.
|
ESANN | 2023 | 0 |
| Efficient classification learning of biochemical structured data by means of relevance weighting for sensoric response features.
|
ESANN | 2022 | 5 |
| Tutorial - Machine Learning and Information Theoretic Methods for Molecular Biology and Medicine.
|
ESANN | 2022 | 0 |
| Prototype-based One-Class-Classification Learning Using Local Representations.
|
IJCNN | 2022 | 4 |
| RecLVQ: Recurrent Learning Vector Quantization.
|
ESANN | 2021 | 0 |
| The Coming of Age of Interpretable and Explainable Machine Learning Models.
|
ESANN | 2021 | 52 |
| The LVQ-based Counter Propagation Network - an Interpretable Information Bottleneck Approach.
|
ESANN | 2021 | 3 |
| Fast Adversarial Robustness Certification of Nearest Prototype Classifiers for Arbitrary Seminorms.
|
NIPS/NeurIPS | 2020 | 27 |
| Quantum-Inspired Learning Vector Quantization for Classification Learning.
|
ESANN | 2020 | 8 |
| DropConnect for Evaluation of Classification Stability in Learning Vector Quantization.
|
ESANN | 2019 | 3 |
| Classification-by-Components: Probabilistic Modeling of Reasoning over a Set of Components.
|
NIPS/NeurIPS | 2019 | 28 |
| Statistical physics of learning and inference.
|
ESANN | 2019 | 4 |
| Reliable Patient Classification in Case of Uncertain Class Labels Using a Cross-Entropy Approach.
|
ESANN | 2018 | 5 |
| Transfer learning in classification based on manifolc. models and its relation to tangent metric learning.
|
IJCNN | 2017 | 11 |
| Biomedical data analysis in translational research: integration of expert knowledge and interpretable models.
|
ESANN | 2017 | 10 |
| Adaptive dissimilarity weighting for prototype-based classification optimizing mixtures of dissimilarities.
|
ESANN | 2016 | 7 |
| Adaptive tangent distances in generalized learning vector quantization for transformation and distortion invariant classification learning.
|
IJCNN | 2016 | 20 |
| Learning matrix quantization and variants of relevance learning.
|
ESANN | 2015 | 4 |
| Stationarity of Matrix Relevance LVQ.
|
IJCNN | 2015 | 36 |
| Median-LVQ for classification of dissimilarity data based on ROC-optimization.
|
ESANN | 2015 | 1 |
| Optimization of General Statistical Accuracy Measures for Classification Based on Learning Vector Quantization.
|
ESANN | 2014 | 12 |
| Supervised Generative Models for Learning Dissimilarity Data.
|
ESANN | 2014 | 6 |
| Applications of lp-Norms and their Smooth Approximations for Gradient Based Learning Vector Quantization.
|
ESANN | 2014 | 68 |
| Recent trends in learning of structured and non-standard data.
|
ESANN | 2014 | 0 |
| Utilization of Chemical Structure Information for Analysis of Spectra Composites.
|
ESANN | 2014 | 2 |
| Border sensitive fuzzy vector quantization in semi-supervised learning.
|
ESANN | 2013 | 2 |
| Regularization in relevance learning vector quantization using l1-norms.
|
ESANN | 2013 | 6 |
| Processing Hyperspectral Data in Machine Learning.
|
ESANN | 2013 | 9 |
| Non-Euclidean independent component analysis and Oja's learning.
|
ESANN | 2013 | 5 |
| A sparse kernelized matrix learning vector quantization model for human activity recognition.
|
ESANN | 2013 | 33 |
| About analysis and robust classification of searchlight fMRI-data using machine learning classifiers.
|
IJCNN | 2013 | 1 |
| Integration of Structural Expert Knowledge about Classes for Classification Using the Fuzzy Supervised Neural Gas.
|
ESANN | 2012 | 6 |
| Recent developments in clustering algorithms.
|
ESANN | 2012 | 12 |
| Modified Conn-Index for the evaluation of fuzzy clusterings.
|
ESANN | 2012 | 4 |
| Unmixing Hyperspectral Images with Fuzzy Supervised Self-Organizing Maps.
|
ESANN | 2012 | 5 |
| Large margin linear discriminative visualization by Matrix Relevance Learning.
|
IJCNN | 2012 | 20 |
| Mathematical Foundations of the Self Organized Neighbor Embedding (SONE) for Dimension Reduction and Visualization.
|
ESANN | 2011 | 8 |
| Generalized functional relevance learning vector quantization.
|
ESANN | 2011 | 12 |
| Optimization of Parametrized Divergences in Fuzzy c-Means.
|
ESANN | 2011 | 6 |
| Information theory related learning.
|
ESANN | 2011 | 5 |
| Magnification in divergence based neural maps.
|
IJCNN | 2011 | 3 |
| Multispectral image characterization by partial generalized covariance.
|
ESANN | 2011 | 4 |
| Multivariate class labeling in Robust Soft LVQ.
|
ESANN | 2011 | 12 |
| Extending FSNPC to handle data points with fuzzy class assignments.
|
ESANN | 2010 | 4 |
| Regularization in matrix relevance learning.
|
IEEE Trans. Neural Networks | 2010 | 102 |
| Sparse representation of data.
|
ESANN | 2010 | 2 |
| Divergence based Learning Vector Quantization.
|
ESANN | 2010 | 20 |
| Exploratory Observation Machine (XOM) with Kullback-Leibler Divergence for Dimensionality Reduction and Visualization.
|
ESANN | 2010 | 73 |
| Learning vector quantization for heterogeneous structured data.
|
ESANN | 2010 | 12 |
| Neural Maps and Learning Vector Quantization - Theory and Applications.
|
ESANN | 2009 | 1 |
| Median Variant of Fuzzy c-Means.
|
ESANN | 2009 | 4 |
| Fuzzy Fleiss-kappa for Comparison of Fuzzy Classifiers.
|
ESANN | 2009 | 8 |
| Machine learning approches and pattern recognition for spectral data.
|
ESANN | 2008 | 14 |
| Metric adaptation for supervised attribute rating.
|
ESANN | 2008 | 1 |
| Generalized matrix learning vector quantizer for the analysis of spectral data.
|
ESANN | 2008 | 19 |
| Magnification Control in Relational Neural Gas.
|
ESANN | 2008 | 5 |
| Intuitive Clustering of Biological Data.
|
IJCNN | 2007 | 5 |
| Visualization of Fuzzy Information in Fuzzy-Classification for Image Segmentation using MDS.
|
ESANN | 2007 | 11 |
| How to process uncertainty in machine learning?.
|
ESANN | 2007 | 23 |
| Explicit Magnification Control of Self-Organizing Maps for "Forbidden" Data.
|
IEEE Trans. Neural Networks | 2007 | 0 |
| Neural networks and machine learning in bioinformatics - theory and applications.
|
ESANN | 2006 | 23 |
| Fuzzy image segmentation with Fuzzy Labelled Neural Gas.
|
ESANN | 2006 | 17 |
| Magnification control for batch neural gas.
|
ESANN | 2006 | 0 |
| Margin based Active Learning for LVQ Networks.
|
ESANN | 2006 | 0 |
| Classification using non-standard metrics.
|
ESANN | 2005 | 24 |
| Relevance learning for mental disease classification.
|
ESANN | 2005 | 4 |
| Generalized Relevance LVQ with Correlation Measures for Biological Data.
|
ESANN | 2005 | 5 |
| Theory and applications of neural maps.
|
ESANN | 2004 | 14 |
| Mathematical Aspects of Neural Networks.
|
ESANN | 2003 | 41 |
| Magnification Control in Winner Relaxing Neural Gas.
|
ESANN | 2003 | 0 |
| Exploratory Data Analysis in Medicine and Bioinformatics.
|
ESANN | 2002 | 2 |
| Batch-RLVQ.
|
ESANN | 2002 | 5 |
| Learning Vector Quantization for Multimodal Data.
|
ICANN | 2002 | 18 |
| Rule Extraction from Self-Organizing Networks.
|
ICANN | 2002 | 28 |
| Evolutionary algorithms and neural networks in hybrid systems.
|
ESANN | 2001 | 12 |
| Input pruning for neural gas architectures.
|
ESANN | 2001 | 4 |
| Neural networks approaches in medicine - a review of actual developments.
|
ESANN | 2000 | 11 |
| Parallel Evolutionary Algorithms with SOM-Like Migration and its Application to VLSI-Design.
|
IJCNN | 2000 | 6 |
| Benefits and limits of the self-organizing map and its variants in the area of satellite remote sensoring processing.
|
ESANN | 1999 | 13 |
| Magnification control in neural maps.
|
ESANN | 1998 | 14 |
| Topology preservation in self-organizing feature maps: exact definition and measurement.
|
IEEE Trans. Neural Networks | 1997 | 366 |
| Vector Quantization by Optimal Neural Gas.
|
ICANN | 1997 | 30 |
| Growing a hypercubical output space in a self-organizing feature map.
|
IEEE Trans. Neural Networks | 1997 | 150 |
| Measuring topology preservation in maps of real-world data.
|
ESANN | 1997 | 7 |