Get started
Author

David Nebel

Observed names: D. Nebel, Nebel, David
OpenAlex ID: A5088903370
Aspects in Classification Learning - Review of Recent Developments in Learning Vector Quantization
2014 · M. Kaden, M. Lange, et al. · Foundations of Computing and Decision Sciences · 56
PDF
Types of (dis-)similarities and adaptive mixtures thereof for improved classification learning
2017 · D. Nebel, M. Kaden, et al. · Neurocomputing · 27
Median variants of learning vector quantization for learning of dissimilarity data
2015 · David Nebel, Barbara Hammer, et al. · Neurocomputing · 24
Investigation of Activation Functions for Generalized Learning Vector Quantization
2019 · Thomas Villmann, Jensun Ravichandran, et al. · Advances in intelligent systems and computing · 17
Rejection Strategies for Learning Vector Quantization – A Comparison of Probabilistic and Deterministic Approaches
2014 · Lydia Fischer, David Nebel, et al. · Advances in intelligent systems and computing · 17
Building the library of RNA 3D nucleotide conformations using the clustering approach
2015 · Tomasz Zok, Maciej Antczak, et al. · International Journal of Applied Mathematics and Computer Science · 15
PDF
Generative versus Discriminative Prototype Based Classification
2014 · Barbara Hammer, David Nebel, et al. · Advances in intelligent systems and computing · 14
Differentiable Kernels in Generalized Matrix Learning Vector Quantization
2012 · Marika Kastner, David Nebel, et al. · International Conference on Machine Learning and Applications · 14
PDF
A Median Variant of Generalized Learning Vector Quantization
2013 · David Nebel, Barbara Hammer, et al. · Lecture notes in computer science · 11
Learning Vector Quantization with Adaptive Cost-Based Outlier-Rejection
2015 · Thomas Villmann, Marika Kaden, et al. · Lecture notes in computer science · 8
Adaptive Hausdorff Distances and Tangent Distance Adaptation for Transformation Invariant Classification Learning
2016 · Sascha Saralajew, David Nebel, et al. · Lecture notes in computer science · 6
ICMLA Face Recognition Challenge -- Results of the Team Computational Intelligence Mittweida
2012 · Thomas Villmann, Marika Kastner, et al. · International Conference on Machine Learning and Applications · 6
Non-euclidean Principal Component Analysis for Matrices by Hebbian Learning
2014 · Mandy Lange, David Nebel, et al. · Lecture notes in computer science · 5
Lateral enhancement in adaptive metric learning for functional data
2013 · T. Villmann, M. Kaden, et al. · Neurocomputing · 5
Similarities, Dissimilarities and Types of Inner Products for Data Analysis in the Context of Machine Learning
2016 · Thomas Villmann, Marika Kaden, et al. · Lecture notes in computer science · 4
Adaptive dissimilarity weighting for prototype-based classification optimizing mixtures of dissimilarities.
2016 · Marika Kaden, David Nebel, et al. · The European Symposium on Artificial Neural Networks · 4
Supervised Generative Models for Learning Dissimilarity Data
2014 · David Nebel, Barbara Hammer, et al. · 4
Partial Mutual Information for Classification of Gene Expression Data by Learning Vector Quantization
2014 · Mandy Lange, David Nebel, et al. · Advances in intelligent systems and computing · 4
Activation Functions for Generalized Learning Vector Quantization - A Performance Comparison
2019 · Villmann, Thomas, Ravichandran, John, et al. · arXiv (Cornell University) · 3
PDF
About Learning of Supervised Generative Models for Dissimilarity Data
2013 · David Nebel, Barbara Hammer, et al. · 2
Data dependent evaluation of dissimilarities in nearest prototype vector quantizers regarding their discriminating abilities
2017 · M. Kaden, D. Nebel, et al. · Workshop on Self-Organizing Maps · 1
Optimization of Statistical Evaluation Measures for Classification by Median Learning Vector Quantization
2016 · D. Nebel, T. Villmann · Advances in intelligent systems and computing · 1
Median-LVQ for classification of dissimilarity data based on ROC-optimization.
2015 · David Nebel, Thomas Villmann · The European Symposium on Artificial Neural Networks · 1
Median Variants of Prototype Based Learning Vector Quantization: Methods for Classification of General Proximity Data
2020 · David Nebel · University of Groningen research database (University of Groningen / Centre for Information Technology)
PDF
Works count: 28
Citation count: 249
H-index: 9
I10-index: 9
Year
Topic
Type