Unsupervised Optimal Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Self-organizing maps
Generalized relevance learning vector quantization
Neural Networks - New developments in self-organizing maps
Soft learning vector quantization
Neural Computation
Rademacher and gaussian complexities: risk bounds and structural results
The Journal of Machine Learning Research
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Online and batch learning of pseudo-metrics
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Supervised Neural Gas with General Similarity Measure
Neural Processing Letters
On the Generalization Ability of GRLVQ Networks
Neural Processing Letters
Performance analysis of LVQ algorithms: a statistical physics approach
Neural Networks - 2006 Special issue: Advances in self-organizing maps--WSOM'05
Dynamics and Generalization Ability of LVQ Algorithms
The Journal of Machine Learning Research
Soft nearest prototype classification
IEEE Transactions on Neural Networks
Distance learning in discriminative vector quantization
Neural Computation
Regularization in matrix relevance learning
IEEE Transactions on Neural Networks
Generalized derivative based kernelized learning vector quantization
IDEAL'10 Proceedings of the 11th international conference on Intelligent data engineering and automated learning
Relevance learning in generative topographic mapping
Neurocomputing
Relevance learning in unsupervised vector quantization based on divergences
WSOM'11 Proceedings of the 8th international conference on Advances in self-organizing maps
A general framework for dimensionality reduction for large data sets
WSOM'11 Proceedings of the 8th international conference on Advances in self-organizing maps
Adaptive matrices for color texture classification
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part II
Prototype-based classification of dissimilarity data
IDA'11 Proceedings of the 10th international conference on Advances in intelligent data analysis X
Cluster-based adaptive metric classification
Neurocomputing
The mathematics of divergence based online learning in vector quantization
ANNPR'10 Proceedings of the 4th IAPR TC3 conference on Artificial Neural Networks in Pattern Recognition
A general framework for dimensionality-reducing data visualization mapping
Neural Computation
Relational extensions of learning vector quantization
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
White box classification of dissimilarity data
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part I
Fuzzy supervised self-organizing map for semi-supervised vector quantization
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
Patch processing for relational learning vector quantization
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
Prototype based modelling for ordinal classification
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
Adaptive metric learning vector quantization for ordinal classification
Neural Computation
Texture feature ranking with relevance learning to classify interstitial lung disease patterns
Artificial Intelligence in Medicine
Border-sensitive learning in kernelized learning vector quantization
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advances in computational intelligence - Volume Part I
Artificial Intelligence in Medicine
A Fast Multiclass Classification Algorithm Based on Cooperative Clustering
Neural Processing Letters
Learning vector quantization for (dis-)similarities
Neurocomputing
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We propose a new matrix learning scheme to extend relevance learning vector quantization (RLVQ), an efficient prototype-based classification algorithm, toward a general adaptive metric. By introducing a full matrix of relevance factors in the distance measure, correlations between different features and their importance for the classification scheme can be taken into account and automated, and general metric adaptation takes place during training. In comparison to the weighted Euclidean metric used in RLVQ and its variations, a full matrix is more powerful to represent the internal structure of the data appropriately. Large margin generalization bounds can be transferred to this case, leading to bounds that are independent of the input dimensionality. This also holds for local metrics attached to each prototype, which corresponds to piecewise quadratic decision boundaries. The algorithm is tested in comparison to alternative learning vector quantization schemes using an artificial data set, a benchmark multiclass problem from the VCI repository, and a problem from bioinformatics, the recognition of splice sites for C. elegans.