Vector quantization based approximate spectral clustering of large datasets

Keywords

Cluster analysis, Vector quantization, Spectral clustering, Pattern recognition (psychology), Quantization (signal processing)

References

• Intrinsic Dimension Estimation by Maximum Likelihood in Probabilistic PCACharles Bouveyron, Gilles Celeux, Stéphane Girard — 2010
• Maps for the Visualization of high-dimensional Data SpacesAlfred Ultsch — 2003
• A Random Walks View of Spectral SegmentationMarina Meilă, Jianbo Shi — 2001
• Spectral Graph TheoryFan Chung — 1996
• Self-Organizing MapsTeuvo Kohonen — 1995
• Approximate pairwise clustering for large data sets via sampling plus extensionLiang Wang, Christopher Leckie, Kotagiri Ramamohanarao — 2011
• Spectral methods in machine learning and new strategies for very large datasetsMohamed-Ali Belabbas, Patrick J. Wolfe — 2009
• On clusterings-good, bad and spectralRavi Kannan, Santosh Vempala, Adrian Vetta — 2000
• Spectral clustering with eigenvector selectionTao Xiang, Shaogang Gong — 2008
• Topology representing networksThomas Martinetz, Klaus Schulten — 1994
• Enhanced neural gas network for prototype-based clusteringA. K. Qin, Ponnuthurai Nagaratnam Suganthan — 2005
• Local density adaptive similarity measurement for spectral clusteringXianchao Zhang, Jingwei Li, Hong Yu — 2011
• Generalized relevance learning vector quantizationBarbara Hammer, Thomas Villmann — 2002
• Spectral Clustering Ensemble Applied to SAR Image SegmentationXiangrong Zhang, Licheng Jiao, Fang Liu — 2008
• Graph Based Representations of Density Distribution and Distances for Self-Organizing MapsKadim Taşdemi̇r — 2010
• A Validity Index for Prototype-Based Clustering of Data Sets With Complex Cluster StructuresKadim Taşdemi̇r, Erzsébet Merényi — 2011
• GTM: The Generative Topographic MappingChris Bishop, Markus Svensén, Christopher K. I. Williams — 1998
• Approximate clustering in very large relational dataJames C. Bezdek, Richard J. Hathaway, Jacalyn M. Huband — 2006
• Spectral grouping using the Nystrom methodCharless C. Fowlkes, Serge Belongie, Fan Chung — 2004
• Knowledge discovery in urban environments from fused multi-dimensional imageryErzsenet Merenyi, B. M. Csathó, Kadim Taşdemi̇r — 2007

Cited by

• A parameter-free similarity graph for spectral clusteringTülin İnkaya — 2015
• An Out-of-sample Extension of Sparse Subspace Clustering and Low Rank Representation for Clustering Large Scale Data SetsXi Peng, Lei Zhang, Yi Zhang — 2013
• Neural network-based clustering for agriculture managementKadim Taşdemi̇r, Csaba Wirnhardt — 2012
• An Approximate Spectral Clustering Ensemble for High Spatial Resolution Remote-Sensing ImagesKadim Taşdemi̇r, Yaser Moazzen, İsa Yıldırım — 2015
• Localized Ambient Solidity Separation Algorithm Based Computer User SegmentationXiao Sun, Tongda Zhang, Yueting Chai — 2015
• Approximate spectral clustering for unsupervised agriculture monitoringKadim Taşdemi̇r — 2015
• Multi-prototype local density-based hierarchical clusteringLeonardo Enzo Brito da Silva, Donald C. Wunsch — 2015
• Geodesic Based Similarities for Approximate Spectral ClusteringKadim Taşdemi̇r, Yaser Moazzen, İsa Yıldırım — 2014
• A hybrid similarity measure for approximate spectral clustering of remote sensing imagesKadim Taşdemi̇r — 2013
• Automatic assessment of land parcel identification systems for agricultural managementKadim Taşdemi̇r, Csaba Wirnhardt — 2012
• Geodesic based hybrid similarity criteria for approximate spectral clustering of remote sensing imagesYaser Moazzen, Kadim Taşdemi̇r — 2014
• Unsupervised extraction of greenhouses using WorldView-2 imagesKadim Taşdemi̇r, Dilek Koç-San — 2014
• Grid topologies for the self-organizing mapEzequiel López‐Rubio, Antonio Díaz Ramos — 2014
• Dimensionality Reduction Based Similarity Visualization for Neural GasKadim Taşdemi̇r — 2014
• Sampling based approximate spectral clustering ensemble for unsupervised land cover identificationYaser Moazzen, Berna Örs, Kadim Taşdemi̇r — 2015
• Local density based similarity criterion for clustering of remote-sensing imagesKadim Taşdemi̇r — 2013
• Deflation-based power iteration clusteringAnh Pham The, Nguyen Duc Thang, La The Vinh — 2013
• The use of k-means++ for approximate spectral clustering of large datasetsBerna Örs, Kadim Taşdemi̇r — 2014
• Spectral Clustering with Local Projection Distance MeasurementChen Diao, Aihua Zhang, Bin Wang — 2015
• Unsupervised extraction of greenhouses using approximate spectral clustering ensembleEsma Pala, Kadim Taşdemi̇r, Dilek Koç-San — 2015

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