DocumentCode
257729
Title
Randomized Kaczmarz algorithms: Exact MSE analysis and optimal sampling probabilities
Author
Agaskar, Ameya ; Chuang Wang ; Lu, Yue M.
Author_Institution
Harvard Univ., Cambridge, MA, USA
fYear
2014
fDate
3-5 Dec. 2014
Firstpage
389
Lastpage
393
Abstract
The Kaczmarz method, or the algebraic reconstruction technique (ART), is a popular method for solving large-scale overdetermined systems of equations. Recently, Strohmer et al. proposed the randomized Kaczmarz algorithm, an improvement that guarantees exponential convergence to the solution. This has spurred much interest in the algorithm and its extensions. We provide in this paper an exact formula for the mean squared error (MSE) in the value reconstructed by the algorithm. We also compute the exponential decay rate of the MSE, which we call the "annealed" error exponent. We show that the typical performance of the algorithm is far better than the average performance. We define the "quenched" error exponent to characterize the typical performance. This is far harder to compute than the annealed error exponent, but we provide an approximation that matches empirical results. We also explore optimizing the algorithm\´s row-selection probabilities to speed up the algorithm\´s convergence.
Keywords
mean square error methods; randomised algorithms; sampling methods; ART; algebraic reconstruction technique; annealed error exponent; exact MSE analysis; exponential decay rate; mean squared error analysis; quenched error exponent; randomized Kaczmarz algorithm; sampling probability; Algorithm design and analysis; Annealing; Approximation methods; Convergence; Histograms; Trajectory; Vectors; Kaczmarz Algorithm; Overdetermined linear systems; randomized Kaczmarz algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal and Information Processing (GlobalSIP), 2014 IEEE Global Conference on
Conference_Location
Atlanta, GA
Type
conf
DOI
10.1109/GlobalSIP.2014.7032145
Filename
7032145
Link To Document