David Nebel - researchr alias

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Viewing Publication 1 - 20 from 20

2019

Investigation of Activation Functions for Generalized Learning Vector QuantizationThomas Villmann, Jensun Ravichandran, Andrea Villmann, David Nebel, Marika Kaden. wsom 2020: 179-188 [doi]

2017

Data dependent evaluation of dissimilarities in nearest prototype vector quantizers regarding their discriminating abilitiesMarika Kaden, David Nebel, Friedrich Melchert, Andreas Backhaus, Udo Seiffert, Thomas Villmann. wsom 2017: 220-226 [doi]

Types of (dis-)similarities and adaptive mixtures thereof for improved classification learningDavid Nebel, Marika Kaden, Andrea Villmann, Thomas Villmann. ijon, 268:42-54, 2017. [doi]

2016

2015

2014

Rejection Strategies for Learning Vector Quantization - A Comparison of Probabilistic and Deterministic ApproachesLydia Fischer, David Nebel, Thomas Villmann, Barbara Hammer, Heiko Wersing. wsom 2014: 109-118 [doi]

Generative versus Discriminative Prototype Based ClassificationBarbara Hammer, David Nebel, Martin Riedel, Thomas Villmann. wsom 2014: 123-132 [doi]

Non-euclidean Principal Component Analysis for Matrices by Hebbian LearningMandy Lange, David Nebel, Thomas Villmann. icaisc 2014: 77-88 [doi]

Partial Mutual Information for Classification of Gene Expression Data by Learning Vector QuantizationMandy Lange, David Nebel, Thomas Villmann. wsom 2014: 259-269 [doi]

Supervised Generative Models for Learning Dissimilarity DataDavid Nebel, Barbara Hammer, Thomas Villmann. esann 2014: [doi]

Lateral enhancement in adaptive metric learning for functional dataThomas Villmann, M. Kaden, David Nebel, Martin Riedel. ijon, 131:23-31, 2014. [doi]

2013

A Median Variant of Generalized Learning Vector QuantizationDavid Nebel, Barbara Hammer, Thomas Villmann. iconip 2013: 19-26 [doi]

2012

Differentiable Kernels in Generalized Matrix Learning Vector QuantizationMarika Kästner, David Nebel, Martin Riedel, Michael Biehl, Thomas Villmann. icmla 2012: 132-137 [doi]

ICMLA Face Recognition Challenge - Results of the Team Computational Intelligence MittweidaThomas Villmann, Marika Kästner, David Nebel, Martin Riedel. icmla 2012: 592-595 [doi]

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