Mandy Lange-Geisler

According to our database, Mandy Lange-Geisler authored at least 21 papers between 2012 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Network reliability analysis by means of generalized matrix learning vector quantization.

Klaus Dohmen, Mandy Lange-Geisler, Thomas Villmann

Appl. Netw. Sci., December, 2026

Privacy-preserving nearest prototype classifier.

Ronny Schubert, Thomas Davies, Mandy Lange-Geisler, Klaus Dohmen, Thomas Villmann

Neurocomputing, 2026

Domination Reliability Analysis Based on Graph Features Using Generalized Matrix LVQ.

Mandy Lange-Geisler, Klaus Dohmen, Thomas Villmann

Proceedings of the 34th European Symposium on Artificial Neural Networks, 2026

2025

General Multi-Prime Multi-Power RSA - A Generalization of RSA and CRT-RSA to Regular Integers Modulo n.

Klaus Dohmen, Mandy Lange-Geisler

IACR Cryptol. ePrint Arch., 2025

Learning of Probability Estimates for System and Network Reliability Analysis by Means of Matrix Learning Vector Quantization.

Mandy Lange-Geisler, Klaus Dohmen, Thomas Villmann

Proceedings of the 33rd European Symposium on Artificial Neural Networks, 2025

Towards Learning Vector Quantization in the Setting of Homomorphic Encryption.

Thomas Davies, Ronny Schubert, Mandy Lange-Geisler, Klaus Dohmen, Thomas Villmann

Proceedings of the 33rd European Symposium on Artificial Neural Networks, 2025

2024

Knowledge Integration in Vector Quantization Models and Corresponding Structured Covariance Estimation.

Marika Kaden, Julius Voigt, Katrin Sophie Bohnsack, Mandy Lange-Geisler, Thomas Villmann

Proceedings of the Advances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and Beyond, 2024

2016

Learning matrix quantization and relevance learning based on Schatten-p-norms.

Andrea Bohnsack, Kristin Domaschke, Marika Kaden, Mandy Lange, Thomas Villmann

Neurocomputing, 2016

2015

Non-Euclidean principal component analysis by Hebbian learning.

Mandy Lange, Michael Biehl, Thomas Villmann

Neurocomputing, 2015

Mathematical Characterization of Sophisticated Variants for Relevance Learning in Learning Matrix Quantization Based on Schatten-p-norms.

Andrea Bohnsack, Kristin Domaschke, Marika Kaden, Mandy Lange, Thomas Villmann

Proceedings of the Artificial Intelligence and Soft Computing, 2015

Learning matrix quantization and variants of relevance learning.

Kristin Domaschke, Marika Kaden, Mandy Lange, Thomas Villmann

Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

2014

Partial Mutual Information for Classification of Gene Expression Data by Learning Vector Quantization.

Mandy Lange, David Nebel, Thomas Villmann

Proceedings of the Advances in Self-Organizing Maps and Learning Vector Quantization, 2014

Non-euclidean Principal Component Analysis for Matrices by Hebbian Learning.

Mandy Lange, David Nebel, Thomas Villmann

Proceedings of the Artificial Intelligence and Soft Computing, 2014

Applications of lp-Norms and their Smooth Approximations for Gradient Based Learning Vector Quantization.

Mandy Lange, Dietlind Zühlke, Olaf Holz, Thomas Villmann

Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Precision-Recall-Optimization in Learning Vector Quantization Classifiers for Improved Medical Classification Systems.

Thomas Villmann, Marika Kaden, Mandy Lange, Paul Sturmer, Wieland Hermann

Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining, 2014

2013

Clustering by Fuzzy Neural Gas and Evaluation of Fuzzy Clusters.

Tina Geweniger, Lydia Fischer, Marika Kaden, Mandy Lange, Thomas Villmann

Comput. Intell. Neurosci., 2013

About analysis and robust classification of searchlight fMRI-data using machine learning classifiers.

Mandy Lange, Marika Kästner, Thomas Villmann

Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

Non-Euclidean independent component analysis and Oja's learning.

Mandy Lange, Michael Biehl, Thomas Villmann

Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

2012

Non-Euclidean Principal Component Analysis and Oja's Learning Rule - Theoretical Aspects.

Michael Biehl, Marika Kästner, Mandy Lange, Thomas Villmann

Proceedings of the Advances in Self-Organizing Maps - 9th International Workshop, 2012

Fuzzy Neural Gas for Unsupervised Vector Quantization.

Thomas Villmann, Tina Geweniger, Marika Kästner, Mandy Lange

Proceedings of the Artificial Intelligence and Soft Computing, 2012

Modified Conn-Index for the evaluation of fuzzy clusterings.

Tina Geweniger, Marika Kästner, Mandy Lange, Thomas Villmann

Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012