David Nebel - RankMe

21 papers B 3Journal 5Unranked 13

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