Histogram-based embedding for learning on statistical manifolds
暂无分享,去创建一个
[1] Carlo Vercellis,et al. A comparative study of nonlinear manifold learning methods for cancer microarray data classification , 2013, Expert Syst. Appl..
[2] Eric O. Postma,et al. Dimensionality Reduction: A Comparative Review , 2008 .
[3] 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.
[4] Frank Nielsen,et al. Pattern Learning and Recognition on Statistical Manifolds: An Information-Geometric Review , 2013, SIMBAD.
[5] Gregory Piatetsky-Shapiro,et al. High-Dimensional Data Analysis: The Curses and Blessings of Dimensionality , 2000 .
[6] Matthew Chalmers,et al. Fast Multidimensional Scaling Through Sampling, Springs and Interpolation , 2003, Inf. Vis..
[7] Michael Barbehenn,et al. A Note on the Complexity of Dijkstra's Algorithm for Graphs with Weighted Vertices , 1998, IEEE Trans. Computers.
[8] Glen D Meeden,et al. Selecting the number of bins in a histogram: A decision theoretic approach , 1997 .
[9] Xiuwen Liu,et al. A Computational Approach to Fisher Information Geometry with Applications to Image Analysis , 2005, EMMCVPR.
[10] Guy Lebanon. Information Geometry, the Embedding Principle, and Document Classification , 2005 .
[11] Shun-ichi Amari,et al. Methods of information geometry , 2000 .
[12] D. Donoho,et al. Hessian Eigenmaps : new locally linear embedding techniques for high-dimensional data , 2003 .
[13] Alfred O. Hero,et al. FINE: Fisher Information Nonparametric Embedding , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[14] Peter J. Bickel,et al. Maximum Likelihood Estimation of Intrinsic Dimension , 2004, NIPS.
[15] Yuan Yan Tang,et al. Multiview Hessian discriminative sparse coding for image annotation , 2013, Comput. Vis. Image Underst..
[16] L. J. P. van der Maaten,et al. An Introduction to Dimensionality Reduction Using Matlab , 2007 .
[17] 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.
[18] Anuj Srivastava,et al. Riemannian Analysis of Probability Density Functions with Applications in Vision , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[19] Ronald M. Lesperance,et al. The Gaussian derivative model for spatial-temporal vision: II. Cortical data. , 2001, Spatial vision.
[20] J. Lafferty,et al. Riemannian Geometry and Statistical Machine Learning , 2015 .
[21] LinLin Shen,et al. Gabor wavelets and General Discriminant Analysis for face identification and verification , 2007, Image Vis. Comput..
[22] Kaizhu Huang,et al. m-SNE: Multiview Stochastic Neighbor Embedding , 2011, IEEE Trans. Syst. Man Cybern. Part B.
[23] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .
[24] Shigeru Shinomoto,et al. A Method for Selecting the Bin Size of a Time Histogram , 2007, Neural Computation.
[25] Yue Zhang,et al. Gabor feature-based face recognition on product gamma manifold via region weighting , 2013, Neurocomputing.
[26] Maciej Kamiński,et al. Analysis of multichannel biomedical data. , 2005, Acta neurobiologiae experimentalis.
[27] Joshua B. Tenenbaum,et al. The Isomap Algorithm and Topological Stability , 2002, Science.
[28] S T Roweis,et al. Nonlinear dimensionality reduction by locally linear embedding. , 2000, Science.
[29] A. Lynn Abbott,et al. Dimensionality Reduction and Clustering on Statistical Manifolds , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[30] Larry S. Davis,et al. Efficient Kernel Density Estimation Using the Fast Gauss Transform with Applications to Color Modeling and Tracking , 2003, IEEE Trans. Pattern Anal. Mach. Intell..
[31] Rui Li,et al. The analysis and applications of adaptive-binning color histograms , 2004, Comput. Vis. Image Underst..
[32] Roberto Brunelli,et al. Histograms analysis for image retrieval , 2001, Pattern Recognit..
[33] N. Čencov. Statistical Decision Rules and Optimal Inference , 2000 .
[34] A. Hero,et al. De-Biasing for Intrinsic Dimension Estimation , 2007, 2007 IEEE/SP 14th Workshop on Statistical Signal Processing.
[35] Mikhail Belkin,et al. Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering , 2001, NIPS.
[36] Yue Zhang,et al. Object recognition using Gabor co-occurrence similarity , 2013, Pattern Recognit..
[37] Snigdhansu Chatterjee,et al. High dimensional data analysis using multivariate generalized spatial quantiles , 2011, J. Multivar. Anal..
[38] Weifeng Liu,et al. Multiview Hessian Regularization for Image Annotation , 2013, IEEE Transactions on Image Processing.
[39] Jun Zhang,et al. Statistical manifold as an affine space: A functional equation approach , 2006 .
[40] J. Jost. Riemannian geometry and geometric analysis , 1995 .
[41] Tommy W. S. Chow,et al. Trace Ratio Optimization-Based Semi-Supervised Nonlinear Dimensionality Reduction for Marginal Manifold Visualization , 2013, IEEE Transactions on Knowledge and Data Engineering.
[42] Son Lam Phung,et al. Learning Pattern Classification Tasks with Imbalanced Data Sets , 2009 .
[43] Aggelos K. Katsaggelos,et al. Locally adaptive subspace and similarity metric learning for visual data clustering and retrieval , 2008, Comput. Vis. Image Underst..
[44] Jonathan Goldstein,et al. When Is ''Nearest Neighbor'' Meaningful? , 1999, ICDT.
[45] I. Kazachkov. Surveys in Contemporary Mathematics: Algebraic geometry over Lie algebras , 2007 .
[46] Chia-Feng Juang,et al. Object detection by color histogram-based fuzzy classifier with support vector learning , 2009, Neurocomputing.
[47] 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.
[48] A. Skopenkov. Surveys in Contemporary Mathematics: Embedding and knotting of manifolds in Euclidean spaces , 2006, math/0604045.
[49] Dacheng Tao,et al. m-SNE: Multiview Stochastic Neighbor Embedding , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[50] B. Scholkopf,et al. Fisher discriminant analysis with kernels , 1999, Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468).