Damped Anderson Acceleration With Restarts and Monotonicity Control for Accelerating EM and EM-like Algorithms

Volume: 28, Issue: 4, Pages: 834 - 846
Published: May 28, 2019
Abstract
The expectation-maximization (EM) algorithm is a well-known iterative method for computing maximum likelihood estimates in a variety of statistical problems. Despite its numerous advantages, a main drawback of the EM algorithm is its frequently observed slow convergence which often hinders the application of EM algorithms in high-dimensional problems or in other complex settings. To address the need for more rapidly convergent EM algorithms, we...
Paper Details
Title
Damped Anderson Acceleration With Restarts and Monotonicity Control for Accelerating EM and EM-like Algorithms
Published Date
May 28, 2019
Volume
28
Issue
4
Pages
834 - 846
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