A Dynamic Programming Algorithm for the Fused Lasso and L 0-Segmentation

We propose a dynamic programming algorithm for the one-dimensional Fused Lasso Signal Approximator (FLSA). The proposed algorithm has a linear running time in the worst case. A similar approach is developed for the task of least squares segmentation, and simulations indicate substantial performance...

Full description

Saved in:
Bibliographic Details
Published in:Journal of computational and graphical statistics Vol. 22; no. 2; pp. 246 - 260
Main Author: Johnson, Nicholas A.
Format: Journal Article
Language:English
Published: Taylor & Francis 2013
Subjects:
Optimization
Signal processing
Total variation denoising
Viterbi
ISSN:1061-8600, 1537-2715
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We propose a dynamic programming algorithm for the one-dimensional Fused Lasso Signal Approximator (FLSA). The proposed algorithm has a linear running time in the worst case. A similar approach is developed for the task of least squares segmentation, and simulations indicate substantial performance improvement over existing algorithms. Examples of R and C implementations are provided in the online Supplementary materials, posted on the journal web site.
ISSN:1061-8600
1537-2715
DOI:10.1080/10618600.2012.681238