Classification constrained dimensionality reduction
暂无分享,去创建一个
[1] Alfred O. Hero,et al. Geodesic entropic graphs for dimension and entropy estimation in manifold learning , 2004, IEEE Transactions on Signal Processing.
[2] Stéphane Lafon,et al. Diffusion maps , 2006 .
[3] Nicolas Le Roux,et al. Learning Eigenfunctions Links Spectral Embedding and Kernel PCA , 2004, Neural Computation.
[4] Jianbo Shi,et al. Detecting unusual activity in video , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..
[5] D. Donoho,et al. Hessian eigenmaps: Locally linear embedding techniques for high-dimensional data , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[6] Shuicheng Yan,et al. Graph Embedding and Extensions: A General Framework for Dimensionality Reduction , 2007 .
[7] Tommi S. Jaakkola,et al. Partially labeled classification with Markov random walks , 2001, NIPS.
[8] Bernhard Schölkopf,et al. Nonlinear Component Analysis as a Kernel Eigenvalue Problem , 1998, Neural Computation.
[9] Charles K. Chui,et al. Special issue on diffusion maps and wavelets , 2006 .
[10] W. Torgerson. Multidimensional scaling: I. Theory and method , 1952 .
[11] J. Franklin,et al. The elements of statistical learning: data mining, inference and prediction , 2005 .
[12] Mikhail Belkin,et al. Laplacian Eigenmaps for Dimensionality Reduction and Data Representation , 2003, Neural Computation.
[13] Nicolas Le Roux,et al. Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering , 2003, NIPS.
[14] J. Tenenbaum,et al. A global geometric framework for nonlinear dimensionality reduction. , 2000, Science.
[15] S T Roweis,et al. Nonlinear dimensionality reduction by locally linear embedding. , 2000, Science.
[16] Kilian Q. Weinberger,et al. Unsupervised Learning of Image Manifolds by Semidefinite Programming , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..
[17] H. Zha,et al. Principal manifolds and nonlinear dimensionality reduction via tangent space alignment , 2004, SIAM J. Sci. Comput..
[18] Mikhail Belkin,et al. Semi-Supervised Learning on Riemannian Manifolds , 2004, Machine Learning.
[19] Susan A. Murphy,et al. Monographs on statistics and applied probability , 1990 .
[20] Anil K. Jain,et al. Algorithms for Clustering Data , 1988 .
[21] M. Aizerman,et al. Theoretical Foundations of the Potential Function Method in Pattern Recognition Learning , 1964 .
[22] Alfred O. Hero,et al. On Dimensionality Reduction for Classification and its Application , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.