A generalized Dantzig selector with shrinkage tuning

By Gareth M. James, Peter Radchenko. 2009

83 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Statistics and Probability

Citations in the corpus

Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data (2016, methodology): “The Gaussian widths of such sub-spaces can be used as a regularization term in techniques such as the generalized Dantzig selector [60], [61].”
Improved variable selection with Forward-Lasso adaptive shrinkage (2011, background): “A few examples include SCAD [Fan and Li (2001)], the Elastic Net [Zou and Hastie (2005)], the Adaptive Lasso [Zou (2006)], the Dantzig selector [Candes and Tao (2007)], the Relaxed Lasso [Meinshausen (2007)], VISA [Radchenko and James (2008)] and the Double Dantzig [James and Radchenko (2009)].”
Generalized Dantzig Selector: Application to the k-support norm (2014, methodology): “For the L1-norm Dantzig selector, [3] proposed a primal-dual interior point method since the optimization is a linear program.”
The Discrete Dantzig Selector: Estimating Sparse Linear Models via Mixed Integer Linear Optimization (2015, background): “sparse linear models, as the data-fidelity parameter is allowed to vary [8], and allows a natural extension to more general response distributions [13].”
DASSO: connections between the Dantzig selector and lasso (2009, methodology): “The final two methods, double Dantzig and double lasso, use ideas that were proposed in James and Radchenko (2008) and Meinshausen (2007).”
Some sharp performance bounds for least squares regression with L1 regularization (2009, methodology): “A related method, called relaxed Lasso, was proposed recently by Meinshausen [16], which is similar to a two-stage Dantzig selector in [4] (also see [ 12 ] for a more detailed study).”
The Dantzig Selector in Cox's Proportional Hazards Model (2009, unknown): “Note also that the result of lemma 1 is taken for granted in the extension of the DS to the class of generalized linear models (GLMs) derived by James & Radchenko (2009), but it is not automatically true.”