Topology representing networks
Neural Networks
Self-organizing maps
GTM: the generative topographic mapping
Neural Computation
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generalized relevance learning vector quantization
Neural Networks - New developments in self-organizing maps
Spectral Grouping Using the Nyström Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
On clusterings: Good, bad and spectral
Journal of the ACM (JACM)
Neural maps in remote sensing image analysis
Neural Networks - 2003 Special issue: Neural network analysis of complex scientific data: Astronomy and geosciences
Approximate clustering in very large relational data: Research Articles
International Journal of Intelligent Systems
A survey of kernel and spectral methods for clustering
Pattern Recognition
Spectral clustering with eigenvector selection
Pattern Recognition
Selective sampling for approximate clustering of very large data sets
International Journal of Intelligent Systems
Approximate Spectral Clustering
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Fast approximate spectral clustering
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Exploiting data topology in visualization and clustering of self-organizing maps
IEEE Transactions on Neural Networks
Enhanced neural gas network for prototype-based clustering
Pattern Recognition
Graph based representations of density distribution and distances for self-organizing maps
IEEE Transactions on Neural Networks
Enabling scalable spectral clustering for image segmentation
Pattern Recognition
Approximate pairwise clustering for large data sets via sampling plus extension
Pattern Recognition
Local density adaptive similarity measurement for spectral clustering
Pattern Recognition Letters
Parallel Spectral Clustering in Distributed Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Explicit Magnification Control of Self-Organizing Maps for “Forbidden” Data
IEEE Transactions on Neural Networks
`Neural-gas' network for vector quantization and its application to time-series prediction
IEEE Transactions on Neural Networks
A Validity Index for Prototype-Based Clustering of Data Sets With Complex Cluster Structures
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Deflation-based power iteration clustering
Applied Intelligence
Local information-based fast approximate spectral clustering
Pattern Recognition Letters
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Spectral partitioning, recently popular for unsupervised clustering, is infeasible for large datasets due to its computational complexity and memory requirement. Therefore, approximate spectral clustering of data representatives (selected by various sampling methods) was used. Alternatively, we propose to use neural networks (self-organizing maps and neural gas), which are shown successful in quantization with small distortion, as preliminary sampling for approximate spectral clustering (ASC). We show that they usually outperform k-means sampling (which was shown superior to various sampling methods), in terms of clustering accuracy obtained by ASC. More importantly, for quantization based ASC, we introduce a local density-based similarity measure - constructed without any user-set parameter - which achieves accuracies superior to the accuracies of commonly used distance based similarity.