David Nebel

According to our database1, David Nebel authored at least 19 papers between 2012 and 2017.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2017
Types of (dis-)similarities and adaptive mixtures thereof for improved classification learning.
Neurocomputing, 2017

Data dependent evaluation of dissimilarities in nearest prototype vector quantizers regarding their discriminating abilities.
Proceedings of the 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, 2017

2016
Optimization of Statistical Evaluation Measures for Classification by Median Learning Vector Quantization.
Proceedings of the Advances in Self-Organizing Maps and Learning Vector Quantization, 2016

Adaptive Hausdorff Distances and Tangent Distance Adaptation for Transformation Invariant Classification Learning.
Proceedings of the Neural Information Processing - 23rd International Conference, 2016

Similarities, Dissimilarities and Types of Inner Products for Data Analysis in the Context of Machine Learning - A Mathematical Characterization.
Proceedings of the Artificial Intelligence and Soft Computing, 2016

Adaptive dissimilarity weighting for prototype-based classification optimizing mixtures of dissimilarities.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

2015
Median variants of learning vector quantization for learning of dissimilarity data.
Neurocomputing, 2015

Building the Library of Rna 3D Nucleotide Conformations Using the Clustering Approach.
Applied Mathematics and Computer Science, 2015

Median-LVQ for classification of dissimilarity data based on ROC-optimization.
Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

Learning Vector Quantization with Adaptive Cost-Based Outlier-Rejection.
Proceedings of the Computer Analysis of Images and Patterns, 2015

2014
Lateral enhancement in adaptive metric learning for functional data.
Neurocomputing, 2014

Partial Mutual Information for Classification of Gene Expression Data by Learning Vector Quantization.
Proceedings of the Advances in Self-Organizing Maps and Learning Vector Quantization, 2014

Generative versus Discriminative Prototype Based Classification.
Proceedings of the Advances in Self-Organizing Maps and Learning Vector Quantization, 2014

Rejection Strategies for Learning Vector Quantization - A Comparison of Probabilistic and Deterministic Approaches.
Proceedings of the Advances in Self-Organizing Maps and Learning Vector Quantization, 2014

Non-euclidean Principal Component Analysis for Matrices by Hebbian Learning.
Proceedings of the Artificial Intelligence and Soft Computing, 2014

Supervised Generative Models for Learning Dissimilarity Data.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

2013
A Median Variant of Generalized Learning Vector Quantization.
Proceedings of the Neural Information Processing - 20th International Conference, 2013

2012
ICMLA Face Recognition Challenge - Results of the Team Computational Intelligence Mittweida.
Proceedings of the 11th International Conference on Machine Learning and Applications, 2012

Differentiable Kernels in Generalized Matrix Learning Vector Quantization.
Proceedings of the 11th International Conference on Machine Learning and Applications, 2012


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