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...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Journal of computational and graphical statistics Ročník 22; číslo 2; s. 246 - 260
Hlavní autor: Johnson, Nicholas A.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Taylor & Francis 2013
Témata:
Optimization
Signal processing
Total variation denoising
Viterbi
ISSN:1061-8600, 1537-2715
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí: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