The Dantzig selector: recovery of signal via ℓ ₁ − αℓ ₂ minimization

Structured Matrix Recovery via the Generalized Dantzig Selector

In recent years, structured matrix recovery problems have gained considerable attention for its real world applications, such as recommender systems and computer vision. Much of the existing work has focused on matrices with low-rank structure, and limited progress has been made on matrices with other types of structure. In this paper we present non-asymptotic analysis for estimation of general...

Analysis of Supersaturated Designs via Dantzig Selector

A supersaturated design is a design whose run size is not enough for estimating all the main effects. It is commonly used in screening experiment, where the goal is to identify sparse and dominant active effects with low cost. In this paper, we study a variable selection method via Dantzig selector, proposed by Candes and Tao (2007), to screen active effects. A graphical procedure and an automa...

The Group Dantzig Selector

We introduce a new method — the group Dantzig selector — for high dimensional sparse regression with group structure, which has a convincing theory about why utilizing the group structure can be beneficial. Under a group restricted isometry condition, we obtain a significantly improved nonasymptotic `2-norm bound over the basis pursuit or the Dantzig selector which ignores the group structure. ...

Discussion of “the Dantzig selector”

Analysis of Supersaturated Designs via the Dantzig Selector

A supersaturated design is a design whose run size is not enough for estimating all the main effects. It is commonly used in screening experiments, where the goals are to identify sparse and dominant active factors with low cost. In this paper, we study a variable selection method via the Dantzig selector, proposed by Candes and Tao (2007), to screen important effects. A graphical procedure and...