Statistical science
Introduction to the Special Issue on Sparsity and Regularization Methods
Jon A. Wellner, Tong Zhang
págs. 447-449
Structured Sparsity through Convex Optimization
Francis Bach, Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski
págs. 450-468
Quasi-Likelihood and/or Robust Estimation in High Dimensions
Sara van de Geer, Patric Müller
págs. 469-480
A Selective Review of Group Selection in High-Dimensional Models
Jian Huang, Patrick Breheny, Shuangge Ma
págs. 481-499
High-Dimensional Regression with Unknown Variance
Christophe Giraud, Sylvie Huet, Nicolas Verzelen
págs. 500-518
Sparse Nonparametric Graphical Models
John Lafferty, Han Liu, Larry Wasserman
págs. 519-537
A Unified Framework for High-Dimensional Analysis of M-Estimators with Decomposable Regularizers
Sahand N. Negahban, Padeep Ravikumar, Martin J. Wainwright, Bin Yu
págs. 538-557
Sparse Estimation by Exponential Weighting
Philippe Rigollet, Alexandre B. Tsybakov
págs. 558-575
A General Theory of Concave Regularization for High-Dimensional Sparse Estimation Problems
Cun-Hui Zhang, Tong Zhang
págs. 576-593
A Conversation with David Findley
Tucker McElroy, Scott H. Holan
págs. 594-606
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