Properties and Iterative Methods for the Q-Lasso
Joint Authors
Xu, Hong Kun
Shahzad, Naseer
Alghamdi, Maryam A.
Alghamdi, Mohammad Ali
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-12-31
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
We introduce the Q-lasso which generalizes the well-known lasso of Tibshirani (1996) with Q a closed convex subset of a Euclidean m-space for some integer m≥1.
This set Q can be interpreted as the set of errors within given tolerance level when linear measurements are taken to recover a signal/image via the lasso.
Solutions of the Q-lasso depend on a tuning parameter γ.
In this paper, we obtain basic properties of the solutions as a function of γ.
Because of ill posedness, we also apply l1-l2 regularization to the Q-lasso.
In addition, we discuss iterative methods for solving the Q-lasso which include the proximal-gradient algorithm and the projection-gradient algorithm.
American Psychological Association (APA)
Alghamdi, Maryam A.& Alghamdi, Mohammad Ali& Shahzad, Naseer& Xu, Hong Kun. 2013. Properties and Iterative Methods for the Q-Lasso. Abstract and Applied Analysis،Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-457448
Modern Language Association (MLA)
Alghamdi, Maryam A.…[et al.]. Properties and Iterative Methods for the Q-Lasso. Abstract and Applied Analysis No. 2013 (2013), pp.1-8.
https://search.emarefa.net/detail/BIM-457448
American Medical Association (AMA)
Alghamdi, Maryam A.& Alghamdi, Mohammad Ali& Shahzad, Naseer& Xu, Hong Kun. Properties and Iterative Methods for the Q-Lasso. Abstract and Applied Analysis. 2013. Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-457448
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-457448
