Error bounds for Bregman denoising and structured natural parameter estimation
暂无分享,去创建一个
Babak Hassibi | Maryam Fazel | James Saunderson | Amin Jalali | B. Hassibi | M. Fazel | J. Saunderson | Amin Jalali
[1] L. Bregman. The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming , 1967 .
[2] Y. Censor,et al. Proximal minimization algorithm withD-functions , 1992 .
[3] Sanjoy Dasgupta,et al. A Generalization of Principal Components Analysis to the Exponential Family , 2001, NIPS.
[4] Heinz H. Bauschke,et al. Bregman Monotone Optimization Algorithms , 2003, SIAM J. Control. Optim..
[5] Inderjit S. Dhillon,et al. Clustering with Bregman Divergences , 2005, J. Mach. Learn. Res..
[6] R. Tibshirani,et al. Sparse inverse covariance estimation with the graphical lasso. , 2008, Biostatistics.
[7] S. Geer. HIGH-DIMENSIONAL GENERALIZED LINEAR MODELS AND THE LASSO , 2008, 0804.0703.
[8] Nenghai Yu,et al. Learning Bregman Distance Functions and Its Application for Semi-Supervised Clustering , 2009, NIPS.
[9] Chunming Zhang,et al. Penalized Bregman divergence for large-dimensional regression and classification. , 2010, Biometrika.
[10] Ambuj Tewari,et al. Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity , 2009, AISTATS.
[11] Martin J. Wainwright,et al. Fast global convergence rates of gradient methods for high-dimensional statistical recovery , 2010, NIPS.
[12] Lu Li,et al. An inexact interior point method for L1-regularized sparse covariance selection , 2010, Math. Program. Comput..
[13] Michael Elad,et al. The Cosparse Analysis Model and Algorithms , 2011, ArXiv.
[14] Pradeep Ravikumar,et al. Sparse inverse covariance matrix estimation using quadratic approximation , 2011, MLSLP.
[15] Pablo A. Parrilo,et al. The Convex Geometry of Linear Inverse Problems , 2010, Foundations of Computational Mathematics.
[16] Daniel J. Hsu,et al. Tail inequalities for sums of random matrices that depend on the intrinsic dimension , 2012 .
[17] Michael I. Jordan,et al. Computational and statistical tradeoffs via convex relaxation , 2012, Proceedings of the National Academy of Sciences.
[18] Michèle Basseville,et al. Divergence measures for statistical data processing - An annotated bibliography , 2013, Signal Process..
[19] Joel A. Tropp,et al. Living on the edge: phase transitions in convex programs with random data , 2013, 1303.6672.
[20] Caroline Uhler,et al. Maximum likelihood estimation for linear Gaussian covariance models , 2014, 1408.5604.
[21] Babak Hassibi,et al. Asymptotically Exact Denoising in Relation to Compressed Sensing , 2013, ArXiv.
[22] Amin Jalali,et al. Convex Optimization Algorithms and Statistical Bounds for Learning Structured Models , 2016 .
[23] Chunming Zhang,et al. Screening-based Bregman divergence estimation with NP-dimensionality , 2016 .