Title :
Accelerating EM by targeted aggressive double extrapolation
Author :
Huang, Han-Shen ; Yang, Bo-Hou ; Lyu, Ren-Yuan ; Hsu, Chun-Nan
Author_Institution :
Inst. of Inf. Sci., Acad. Sinica, Taipei
Abstract :
The Expectation-Maximization (EM) algorithm is one of the most popular algorithms for parameter estimation from incomplete data, but its convergence can be slow for some large-scale or complex problems. Extrapolation methods can effectively accelerate EM, but to ensure stability, the learning rate of extrapolation must be compromised. This paper describes the TJ2aEM method, a targeted extrapolation method that can extrapolate much more aggressively than competing methods without causing instability problems. We analyze its convergence properties and report experimental results.
Keywords :
eigenvalues and eigenfunctions; expectation-maximisation algorithm; extrapolation; parameter estimation; eigenfunctions; eigenvalues; expectation-maximization algorithm; extrapolation method; parameter estimation; targeted aggressive double extrapolation; Acceleration; Algorithm design and analysis; Convergence; Eigenvalues and eigenfunctions; Extrapolation; Information science; Iterative algorithms; Jacobian matrices; Parameter estimation; Upper bound; Acceleration; Convergence of numerical methods; Eigenvalues and eigenfunctions; Extrapolation; Parameter estimation;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-2353-8
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2009.4959907