P. Schneider

发表

Distance Learning in Discriminative Vector Quantization

Michael Biehl, Barbara Hammer, Petra Schneider, 2009, Neural Computation.

University of Groningen Advanced methods for prototype-based classification

P. Schneider, 2017 .

Advanced metric adaptation in Generalized LVQ for classification of mass spectrometry data

Michael Biehl, Frank-Michael Schleif, Barbara Hammer, 2007 .

Analysis of Flow Cytometry Data by Matrix Relevance Learning Vector Quantization

Michael Biehl, Kerstin Bunte, Petra Schneider, 2013, PloS one.

University of Groningen Generalized Derivative Based Kernelized Learning Vector Quantization Schleif,

Michael Biehl, T. Villmann, B. Hammer, 2010 .

Matrix adaptation in discriminative vector quantization

Michael Biehl, Barbara Hammer, Petra Schneider, 2008 .

Proc. 6th International Workshop on Self-Organizing Maps

Michael Biehl, Frank-Michael Schleif, Barbara Hammer, 2007 .

Advances in artificial neural networks, machine learning, and computational intelligence (ESANN 2011)

Luca Oneto, Kerstin Bunte, Nicoló Navarin, 2011, Neurocomputing.

Advances in artificial neural networks, machine learning, and computational intelligence (ESANN 2011)

Luca Oneto, Frank-Michael Schleif, Kerstin Bunte, 2011, Neurocomputing.

Proc. European Symposium on Artificial Neural Networks

Thomas Villmann, Michael Biehl, Frank-Michael Schleif, 2007 .

Advances in artificial neural networks, machine learning, and computational intelligence (ESANN 2011)

Thomas Martinetz, Frank-Michael Schleif, John Aldo Lee, 2011, Neurocomputing.

Incorporating Privileged Information Through Metric Learning

Peter Tiño, Shereen Fouad, Petra Schneider, 2013, IEEE Transactions on Neural Networks and Learning Systems.

Efficient Kernelized Prototype Based Classification

Thomas Villmann, Frank-Michael Schleif, Barbara Hammer, 2011, Int. J. Neural Syst..

Mitotane therapy in adrenocortical cancer induces CYP 3 A 4 and inhibits 5-reductase , explaining the need for personalized glucocorticoid and androgen replacement

F. Beuschlein, J. Bertherat, X. Bertagna, 2012 .

Urine Steroid Metabolomics as a Biomarker Tool for Detecting Malignancy in Adrenal Tumors

Michael Biehl, Martin Fassnacht, David J. Smith, 2011, The Journal of clinical endocrinology and metabolism.

Limited Rank Matrix Learning, discriminative dimension reduction and visualization

Thomas Villmann, Michael Biehl, Frank-Michael Schleif, 2012, Neural Networks.

Adaptive Relevance Matrices in Learning Vector Quantization

Michael Biehl, Barbara Hammer, Petra Schneider, 2009, Neural Computation.

Metric Learning for Prototype-Based Classification

Thomas Villmann, Michael Biehl, Barbara Hammer, 2009, Innovations in Neural Information Paradigms and Applications.

Nonlinear Discriminative Data Visualization

Michael Biehl, Barbara Hammer, Petra Schneider, 2009, ESANN.

Divergence-based classification in learning vector quantization

Thomas Villmann, Michael Biehl, Frank-Michael Schleif, 2011, Neurocomputing.

Discriminative visualization by limited rank matrix learning

Thomas Villmann, Michael Biehl, Frank-Michael Schleif, 2008 .

Large margin linear discriminative visualization by Matrix Relevance Learning

Thomas Villmann, Michael Biehl, Frank-Michael Schleif, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

Adaptive Matrix Metrics for Attribute Dependence Analysis in Differential High-Throughput Data

Michael Biehl, J. Keilwagen, T. Villmann, 2008 .

University of Groningen Adaptive Matrix Metrics for Attribute Dependence Analysis in Differential High-Throughput Data Strickert,

M. Biehl, J. Keilwagen, T. Villmann, 2008 .

Stationarity of Matrix Relevance LVQ

Thomas Villmann, Michael Biehl, Frank-Michael Schleif, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Divergence based Learning Vector Quantization

Thomas Villmann, Michael Biehl, Frank-Michael Schleif, 2010, ESANN.

Incorporating Privileged Information Through Metric Learning

P. Tiňo, Somak Raychaudhury, P. Schneider, 2013, IEEE Transactions on Neural Networks and Learning Systems.

Adaptive Relevance Matrices in Learning Vector Quantization

Michael Biehl, B. Hammer, P. Schneider, 2009, Neural Computation.

Discriminatory Data Mapping by Matrix-Based Supervised Learning Metrics

Thomas Villmann, Michael Biehl, Barbara Hammer, 2008, ANNPR.