The generalized lasso is reducible to a subspace constrained lasso

Hao Xu, David J. Eis, Peter J. Ramadge

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

We investigate connections between the generalized lasso and the standard lasso problem. We show by an efficient direct construction, that the generalized lasso problem is reducible to a subspace constrained lasso. We then derive the dual of the subspace constrained lasso. This dual problem can be projected to the dual of a standard lasso problem with a modified dictionary. Finally, we discuss the application of these ideas to image approximation using the 2D fused lasso.

Original languageEnglish (US)
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages3268-3272
Number of pages5
DOIs
StatePublished - Oct 18 2013
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: May 26 2013May 31 2013

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
Country/TerritoryCanada
CityVancouver, BC
Period5/26/135/31/13

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Keywords

  • Lagrange dual
  • Sparsity
  • lasso
  • regularized regression

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