Clustering and Embedding Using Commute Times
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[1] Ann B. Lee,et al. Geometric diffusions as a tool for harmonic analysis and structure definition of data: diffusion maps. , 2005, Proceedings of the National Academy of Sciences of the United States of America.
[2] Ronald R. Coifman,et al. Diffusion Maps, Spectral Clustering and Eigenfunctions of Fokker-Planck Operators , 2005, NIPS.
[3] Kenichi Kanatani,et al. Outlier removal for motion tracking by subspace separation , 2002 .
[4] Stéphane Lafon,et al. Diffusion maps , 2006 .
[5] Jianbo Shi,et al. A Random Walks View of Spectral Segmentation , 2001, AISTATS.
[6] Amnon Shashua,et al. A unifying approach to hard and probabilistic clustering , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[7] Ying Wu,et al. Inference of multiple subspaces from high-dimensional data and application to multibody grouping , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..
[8] François Fouss,et al. The Principal Components Analysis of a Graph, and Its Relationships to Spectral Clustering , 2004, ECML.
[9] Kim L. Boyer,et al. Quantitative measures of change based on feature organization: eigenvalues and eigenvectors , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[10] Jitendra Malik,et al. Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[11] François Fouss,et al. An Experimental Investigation of Graph Kernels on a Collaborative Recommendation Task , 2006, Sixth International Conference on Data Mining (ICDM'06).
[12] Carlo Tomasi,et al. Good features to track , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.
[13] Guy L. Scott,et al. Feature grouping by 'relocalisation' of eigenvectors of the proximity matrix , 1990, BMVC.
[14] Edwin R. Hancock,et al. Image Segmentation using Commute Times , 2005, BMVC.
[15] Naoyuki Ichimura. Motion segmentation based on factorization method and discriminant criterion , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[16] J. MacQueen. Some methods for classification and analysis of multivariate observations , 1967 .
[17] Marcello Pelillo,et al. Dominant sets and hierarchical clustering , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[18] Jin Hyeong Park,et al. Spectral Clustering for Robust Motion Segmentation , 2004, ECCV.
[19] Xiaofei He,et al. Locality Preserving Projections , 2003, NIPS.
[20] Kenichi Kanatani,et al. Motion segmentation by subspace separation and model selection , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.
[21] KanadeTakeo,et al. A Multibody Factorization Method for Independently Moving Objects , 1998 .
[22] Michael I. Jordan,et al. On Spectral Clustering: Analysis and an algorithm , 2001, NIPS.
[23] Ying Wu,et al. Multibody grouping via orthogonal subspace decomposition , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.
[24] Ann B. Lee,et al. Diffusion maps and coarse-graining: a unified framework for dimensionality reduction, graph partitioning, and data set parameterization , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[25] S T Roweis,et al. Nonlinear dimensionality reduction by locally linear embedding. , 2000, Science.
[26] M. Pavan,et al. A new graph-theoretic approach to clustering and segmentation , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..
[27] Mikhail Belkin,et al. Laplacian Eigenmaps for Dimensionality Reduction and Data Representation , 2003, Neural Computation.
[28] Shing-Tung Yau,et al. Discrete Green's Functions , 2000, J. Comb. Theory A.
[29] Andrew B. Kahng,et al. New spectral methods for ratio cut partitioning and clustering , 1991, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..
[30] Yair Weiss,et al. Multibody factorization with uncertainty and missing data using the EM algorithm , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..
[31] C. W. Gear,et al. Multibody Grouping from Motion Images , 1998, International Journal of Computer Vision.
[32] Takeo Kanade,et al. A multi-body factorization method for motion analysis , 1995, Proceedings of IEEE International Conference on Computer Vision.
[33] Lihi Zelnik-Manor,et al. Degeneracies, dependencies and their implications in multi-body and multi-sequence factorizations , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..
[34] Takeo Kanade,et al. A Multibody Factorization Method for Independently Moving Objects , 1998, International Journal of Computer Vision.
[35] Jan Poland,et al. Amplifying the Block Matrix Structure for Spectral Clustering. , 2005 .
[36] P. Anandan,et al. Factorization with Uncertainty , 2000, International Journal of Computer Vision.
[37] J. Tenenbaum,et al. A global geometric framework for nonlinear dimensionality reduction. , 2000, Science.
[38] Mikhail Belkin,et al. Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering , 2001, NIPS.
[39] H. Hotelling. Analysis of a complex of statistical variables into principal components. , 1933 .
[40] Risi Kondor,et al. Diffusion kernels on graphs and other discrete structures , 2002, ICML 2002.
[41] John D. Lafferty,et al. Diffusion Kernels on Graphs and Other Discrete Input Spaces , 2002, ICML.
[42] Pietro Perona,et al. A Factorization Approach to Grouping , 1998, ECCV.
[43] Yair Weiss,et al. Segmentation using eigenvectors: a unifying view , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[44] Kenichi Kanatani,et al. Multi-Stage Unsupervised Learning for Multi-Body Motion Segmentation , 2004, IEICE Trans. Inf. Syst..
[45] Bernhard Schölkopf,et al. Nonlinear Component Analysis as a Kernel Eigenvalue Problem , 1998, Neural Computation.