TY - JOUR
T1 - A fast splitting method tailored for Dantzig selector
AU - He, Hongjin
AU - Cai, Xingju
AU - Han, Deren
N1 - Publisher Copyright:
© 2015, Springer Science+Business Media New York.
PY - 2015/11/1
Y1 - 2015/11/1
N2 - In this paper, we introduce a splitting method for solving Dantzig selector problem, a new linear regression model that was extensively studied in the literature in the past few years. The new method is very simple in the sense that, per iteration, it only performs a projection onto a box, and does some matrix-vector products. We prove the global convergence of the method and report some promising numerical results, which demonstrate that the new method is competitive with some state-of-the-art methods recently developed in the literature.
AB - In this paper, we introduce a splitting method for solving Dantzig selector problem, a new linear regression model that was extensively studied in the literature in the past few years. The new method is very simple in the sense that, per iteration, it only performs a projection onto a box, and does some matrix-vector products. We prove the global convergence of the method and report some promising numerical results, which demonstrate that the new method is competitive with some state-of-the-art methods recently developed in the literature.
KW - Alternating direction method of multipliers
KW - Dantzig selector
KW - Fast splitting method
KW - Linear regression
UR - https://www.scopus.com/pages/publications/84943665712
U2 - 10.1007/s10589-015-9748-2
DO - 10.1007/s10589-015-9748-2
M3 - 文章
AN - SCOPUS:84943665712
SN - 0926-6003
VL - 62
SP - 347
EP - 372
JO - Computational Optimization and Applications
JF - Computational Optimization and Applications
IS - 2
ER -