@inproceedings{9fe34518df10495596711420fed243d8,
title = "Lasso screening with a small regularization parameter",
abstract = "Screening for lasso problems is a means of quickly reducing the size of the dictionary needed to solve a given instance without impacting the optimality of the solution obtained. We investigate a sequential screening scheme using a selected sequence of regularization parameter values decreasing to the given target value. Using analytical and empirical means we give insight on how the values of this sequence should be chosen and show that well designed sequential screening yields significant improvement in dictionary reduction and computational efficiency for lightly regularized lasso problems.",
keywords = "regularized regression, screening, sparse regression",
author = "Yun Wang and Xiang, {Zhen James} and Ramadge, {Peter J.}",
year = "2013",
month = oct,
day = "18",
doi = "10.1109/ICASSP.2013.6638277",
language = "English (US)",
isbn = "9781479903566",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
pages = "3342--3346",
booktitle = "2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings",
note = "2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 ; Conference date: 26-05-2013 Through 31-05-2013",
}