Compressed Least-Squares Regression
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[1] A Tikhonov,et al. Solution of Incorrectly Formulated Problems and the Regularization Method , 1963 .
[2] D. Pollard. Convergence of stochastic processes , 1984 .
[3] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[4] L. Trefethen,et al. Numerical linear algebra , 1997 .
[5] Michael A. Saunders,et al. Atomic Decomposition by Basis Pursuit , 1998, SIAM J. Sci. Comput..
[6] S. Mallat. A wavelet tour of signal processing , 1998 .
[7] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[8] Tong Zhang,et al. Covering Number Bounds of Certain Regularized Linear Function Classes , 2002, J. Mach. Learn. Res..
[9] Adam Krzyzak,et al. A Distribution-Free Theory of Nonparametric Regression , 2002, Springer series in statistics.
[10] Dimitris Achlioptas,et al. Database-friendly random projections: Johnson-Lindenstrauss with binary coins , 2003, J. Comput. Syst. Sci..
[11] Y. Ritov,et al. Persistence in high-dimensional linear predictor selection and the virtue of overparametrization , 2004 .
[12] Avrim Blum,et al. Random Projection, Margins, Kernels, and Feature-Selection , 2005, SLSFS.
[13] Emmanuel J. Candès,et al. Signal recovery from random projections , 2005, IS&T/SPIE Electronic Imaging.
[14] Richard G. Baraniuk,et al. Detection and estimation with compressive measurements , 2006 .
[15] David L Donoho,et al. Compressed sensing , 2006, IEEE Transactions on Information Theory.
[16] Bernard Chazelle,et al. Approximate nearest neighbors and the fast Johnson-Lindenstrauss transform , 2006, STOC '06.
[17] S. Rosset,et al. Piecewise linear regularized solution paths , 2007, 0708.2197.
[18] Larry A. Wasserman,et al. Compressed Regression , 2007, NIPS.
[19] Terence Tao,et al. The Dantzig selector: Statistical estimation when P is much larger than n , 2005, math/0506081.
[20] Benjamin Recht,et al. Random Features for Large-Scale Kernel Machines , 2007, NIPS.
[21] A. Rinaldo,et al. On the asymptotic properties of the group lasso estimator for linear models , 2008 .
[22] Ambuj Tewari,et al. On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization , 2008, NIPS.
[23] R. Calderbank. Compressed Learning : Universal Sparse Dimensionality Reduction and Learning in the Measurement Domain , 2009 .
[24] Tong Zhang. Some sharp performance bounds for least squares regression with L1 regularization , 2009, 0908.2869.
[25] P. Bickel,et al. SIMULTANEOUS ANALYSIS OF LASSO AND DANTZIG SELECTOR , 2008, 0801.1095.
[26] Jean-Yves Audibert,et al. Risk bounds in linear regression through PAC-Bayesian truncation , 2009, 0902.1733.
[27] Philipp Birken,et al. Numerical Linear Algebra , 2011, Encyclopedia of Parallel Computing.