Mandy Lange

发表

Advances in Self-Organizing Maps and Learning Vector Quantization - Proceedings of the 10th International Workshop, WSOM 2014, Mittweida, Germany, July, 2-4, 2014

Thomas Villmann, Frank-Michael Schleif, Marika Kaden, 2014, WSOM.

Aspects in Classification Learning - Review of Recent Developments in Learning Vector Quantization

Thomas Villmann, Martin Riedel, Tina Geweniger, 2014 .

Non-Euclidean principal component analysis by Hebbian learning

Thomas Villmann, Michael Biehl, Mandy Lange, 2015, Neurocomputing.

Hebbian learning approaches based on general inner products and distance measures in non-Euclidean spaces

Mandy Lange, M. Lange, 2019 .

Learning matrix quantization and variants of relevance learning

Thomas Villmann, Marika Kaden, Mandy Lange, 2015, ESANN.

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

Thomas Villmann, Michael Biehl, Marika Kaden, 2012, WSOM.

Non-euclidean Principal Component Analysis for Matrices by Hebbian Learning

Thomas Villmann, David Nebel, Mandy Lange, 2014, ICAISC.

Fuzzy Neural Gas for Unsupervised Vector Quantization

Thomas Villmann, Tina Geweniger, Marika Kaden, 2012, ICAISC.

Non-Euclidean independent component analysis and Oja's learning

Thomas Villmann, Michael Biehl, Mandy Lange, 2013, ESANN.

Proc. 21st Europ. Symp. Artificial Neural Networks (ESANN)

Michael Biehl, T. Villmann, Mandy Lange, 2013 .

Modified Conn-Index for the evaluation of fuzzy clusterings

Thomas Villmann, Tina Geweniger, Marika Kaden, 2012, ESANN.

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

Thomas Villmann, Marika Kaden, Mandy Lange, 2015, ICAISC.

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

Thomas Villmann, Wieland Hermann, Marika Kaden, 2014, 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM).

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

Thomas Villmann, Marika Kaden, Mandy Lange, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

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

Thomas Villmann, Dietlind Zühlke, Mandy Lange, 2014, ESANN.

Clustering by Fuzzy Neural Gas and Evaluation of Fuzzy Clusters

Thomas Villmann, Tina Geweniger, Marika Kaden, 2013, Comput. Intell. Neurosci..

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

Thomas Villmann, David Nebel, Mandy Lange, 2014, WSOM.