David Nebel

Publication Activity (10 Years)

Years Active: 2012-2019
Publications (10 Years): 8

Top Topics

Metric Learning

Learning Vector Quantization

Tangent Distance

Gene Expression

Top Venues

Publications

Thomas Villmann, Jensun Ravichandran, Andrea Villmann, David Nebel, Marika Kaden
Investigation of Activation Functions for Generalized Learning Vector Quantization. WSOM+ (2019)
Thomas Villmann, John Ravichandran, Andrea Villmann, David Nebel, Marika Kaden
Activation Functions for Generalized Learning Vector Quantization - A Performance Comparison. CoRR (2019)
Marika Kaden, David Nebel, Friedrich Melchert, Andreas Backhaus, Udo Seiffert, Thomas Villmann
Data dependent evaluation of dissimilarities in nearest prototype vector quantizers regarding their discriminating abilities. WSOM (2017)
David Nebel, Marika Kaden, Andrea Villmann, Thomas Villmann
Types of (dis-)similarities and adaptive mixtures thereof for improved classification learning. Neurocomputing 268 (2017)
Sascha Saralajew, David Nebel, Thomas Villmann
Adaptive Hausdorff Distances and Tangent Distance Adaptation for Transformation Invariant Classification Learning. ICONIP (3) (2016)
Thomas Villmann, Marika Kaden, David Nebel, Andrea Bohnsack
Similarities, Dissimilarities and Types of Inner Products for Data Analysis in the Context of Machine Learning - A Mathematical Characterization. ICAISC (2) (2016)
David Nebel, Thomas Villmann
Optimization of Statistical Evaluation Measures for Classification by Median Learning Vector Quantization. WSOM (2016)
Marika Kaden, David Nebel, Thomas Villmann
Adaptive dissimilarity weighting for prototype-based classification optimizing mixtures of dissimilarities. ESANN (2016)
Thomas Villmann, Marika Kaden, David Nebel, Michael Biehl
Learning Vector Quantization with Adaptive Cost-Based Outlier-Rejection. CAIP (2) (2015)
David Nebel, Thomas Villmann
Median-LVQ for classification of dissimilarity data based on ROC-optimization. ESANN (2015)
Tomasz Zok, Maciej Antczak, Martin Riedel, David Nebel, Thomas Villmann, Piotr Lukasiak, Jacek Blazewicz, Marta Szachniuk
Building the Library of Rna 3D Nucleotide Conformations Using the Clustering Approach. Int. J. Appl. Math. Comput. Sci. 25 (3) (2015)
David Nebel, Barbara Hammer, Kathleen Frohberg, Thomas Villmann
Median variants of learning vector quantization for learning of dissimilarity data. Neurocomputing 169 (2015)
Mandy Lange, David Nebel, Thomas Villmann
Non-euclidean Principal Component Analysis for Matrices by Hebbian Learning. ICAISC (1) (2014)
Lydia Fischer, David Nebel, Thomas Villmann, Barbara Hammer, Heiko Wersing
Rejection Strategies for Learning Vector Quantization - A Comparison of Probabilistic and Deterministic Approaches. WSOM (2014)
Thomas Villmann, Marika Kaden, David Nebel, Martin Riedel
Lateral enhancement in adaptive metric learning for functional data. Neurocomputing 131 (2014)
Mandy Lange, David Nebel, Thomas Villmann
Partial Mutual Information for Classification of Gene Expression Data by Learning Vector Quantization. WSOM (2014)
Barbara Hammer, David Nebel, Martin Riedel, Thomas Villmann
Generative versus Discriminative Prototype Based Classification. WSOM (2014)
David Nebel, Barbara Hammer, Thomas Villmann
Supervised Generative Models for Learning Dissimilarity Data. ESANN (2014)
David Nebel, Barbara Hammer, Thomas Villmann
A Median Variant of Generalized Learning Vector Quantization. ICONIP (2) (2013)
Thomas Villmann, Marika Kästner, David Nebel, Martin Riedel
ICMLA Face Recognition Challenge - Results of the Team Computational Intelligence Mittweida. ICMLA (2) (2012)
Marika Kästner, David Nebel, Martin Riedel, Michael Biehl, Thomas Villmann
Differentiable Kernels in Generalized Matrix Learning Vector Quantization. ICMLA (1) (2012)