Iterative Gaussianization: From ICA to Random Rotations
暂无分享,去创建一个
[1] Jean-François Cardoso,et al. Dependence, Correlation and Gaussianity in Independent Component Analysis , 2003, J. Mach. Learn. Res..
[2] Feller William,et al. An Introduction To Probability Theory And Its Applications , 1950 .
[3] Aapo Hyvärinen,et al. Sparse Code Shrinkage: Denoising of Nongaussian Data by Maximum Likelihood Estimation , 1999, Neural Computation.
[4] I. Johnstone,et al. Adapting to Unknown Smoothness via Wavelet Shrinkage , 1995 .
[5] Kuldip K. Paliwal,et al. Fast principal component analysis using fixed-point algorithm , 2007, Pattern Recognit. Lett..
[6] P. J. Green,et al. Density Estimation for Statistics and Data Analysis , 1987 .
[7] Lai-Wan Chan,et al. Extended Gaussianization Method for Blind Separation of Post-Nonlinear Mixtures , 2005, Neural Computation.
[8] Valero Laparra,et al. Image Denoising with Kernels Based on Natural Image Relations , 2010, J. Mach. Learn. Res..
[9] D. W. Scott,et al. Multivariate Density Estimation, Theory, Practice and Visualization , 1992 .
[10] Tülay Adali,et al. Complex ICA by Negentropy Maximization , 2008, IEEE Transactions on Neural Networks.
[11] Valero Laparra,et al. Psychophysically Tuned Divisive Normalization Approximately Factorizes the PDF of Natural Images , 2010, Neural Computation.
[12] Eero P. Simoncelli,et al. Image compression via joint statistical characterization in the wavelet domain , 1999, IEEE Trans. Image Process..
[13] Eero P. Simoncelli,et al. Nonlinear Extraction of Independent Components of Natural Images Using Radial Gaussianization , 2009, Neural Computation.
[14] David J. Kriegman,et al. From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose , 2001, IEEE Trans. Pattern Anal. Mach. Intell..
[15] M. Studený,et al. The Multiinformation Function as a Tool for Measuring Stochastic Dependence , 1998, Learning in Graphical Models.
[16] Martin J. Wainwright,et al. Image denoising using scale mixtures of Gaussians in the wavelet domain , 2003, IEEE Trans. Image Process..
[17] Charles M. Grinstead,et al. Introduction to probability , 1999, Statistics for the Behavioural Sciences.
[18] David G. Stork,et al. Pattern Classification (2nd ed.) , 1999 .
[19] Adrian F. M. Smith,et al. BOOK REVIEW: Bayesian Theory , 2001 .
[20] Pierre Moulin,et al. Information-theoretic analysis of interscale and intrascale dependencies between image wavelet coefficients , 2001, IEEE Trans. Image Process..
[21] Eero P. Simoncelli,et al. Nonlinear image representation for efficient perceptual coding , 2006, IEEE Transactions on Image Processing.
[22] Trevor Hastie,et al. The Elements of Statistical Learning , 2001 .
[23] L. Dworsky. An Introduction to Probability , 2008 .
[24] I. Jolliffe. Principal Component Analysis , 2002 .
[25] Robin Sibson,et al. What is projection pursuit , 1987 .
[26] Pierre Comon,et al. How fast is FastICA? , 2006, 2006 14th European Signal Processing Conference.
[27] Ramesh A. Gopinath,et al. Gaussianization , 2000, NIPS.
[28] P. A. P. Moran,et al. An introduction to probability theory , 1968 .
[29] Jason F. Ralph,et al. Automatic Induction of Projection Pursuit Indices , 2010, IEEE Transactions on Neural Networks.
[30] Matthias Bethge,et al. Natural Image Coding in V1: How Much Use Is Orientation Selectivity? , 2008, PLoS Comput. Biol..
[31] John W. Fisher,et al. ICA Using Spacings Estimates of Entropy , 2003, J. Mach. Learn. Res..
[32] Jia Jie. Bayesian denoising of visual images in the wavelet domain , 2003 .
[33] Eero P. Simoncelli,et al. Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.
[34] Shigeo Abe DrEng. Pattern Classification , 2001, Springer London.
[35] Robert P. W. Duin,et al. Support vector domain description , 1999, Pattern Recognit. Lett..
[36] Henry Stark,et al. Probability, Random Processes, and Estimation Theory for Engineers , 1995 .
[37] Allen Gersho,et al. Vector quantization and signal compression , 1991, The Kluwer international series in engineering and computer science.
[38] Luis Gómez-Chova,et al. Urban monitoring using multi-temporal SAR and multi-spectral data , 2006, Pattern Recognit. Lett..
[39] Robert D. Nowak,et al. Wavelet-based image estimation: an empirical Bayes approach using Jeffrey's noninformative prior , 2001, IEEE Trans. Image Process..
[40] R. Moddemeijer. On estimation of entropy and mutual information of continuous distributions , 1989 .
[41] Jacob Cohen. A Coefficient of Agreement for Nominal Scales , 1960 .
[42] Robert Jenssen,et al. Gaussianization: An Efficient Multivariate Density Estimation Technique for Statistical Signal Processing , 2006, J. VLSI Signal Process..
[43] Gustavo Camps-Valls,et al. On the Suitable Domain for SVM Training in Image Coding , 2008, J. Mach. Learn. Res..
[44] Eero P. Simoncelli,et al. A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients , 2000, International Journal of Computer Vision.
[45] Eero P. Simoncelli. Bayesian Denoising of Visual Images in the Wavelet Domain , 1999 .
[46] Ramesh A. Gopinath,et al. Short-time Gaussianization for robust speaker verification , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[47] Gene H. Golub,et al. Matrix computations , 1983 .
[48] John W. Tukey,et al. A Projection Pursuit Algorithm for Exploratory Data Analysis , 1974, IEEE Transactions on Computers.
[49] Jean-Claude Massé,et al. A statistical model for random rotations , 2006 .
[50] Maria L. Rizzo,et al. A new test for multivariate normality , 2005 .
[51] Aapo Hyvärinen,et al. Fast and robust fixed-point algorithms for independent component analysis , 1999, IEEE Trans. Neural Networks.
[52] F. Piazza,et al. A practical Approach Based on Gaussianization for Post-Nonlinear Underdetermined BSS , 2006, 2006 International Conference on Communications, Circuits and Systems.
[53] Francesc J. Ferri,et al. Regularization operators for natural images based on nonlinear perception models , 2006, IEEE Transactions on Image Processing.
[54] Geoffrey E. Hinton,et al. Reducing the Dimensionality of Data with Neural Networks , 2006, Science.
[55] Pierre Comon,et al. Independent component analysis, A new concept? , 1994, Signal Process..