On the slow convergence of EM and VBEM in low-noise linear models

Kaare Brandt Petersen, Ole Winther, Lars Kai Hansen

Abstract

We analyze convergence of the expectation maximization (EM) and variational Bayes EM (VBEM) schemes for parameter estimation in noisy linear models. The analysis shows that both schemes are inefficient in the low-noise limit. The linear model with additive noise includes as special cases independent component analysis, probabilistic principal component analysis, factor analysis, and Kalman filtering. Hence, the results are relevant for many practical applications.

OriginalsprogEngelsk
TidsskriftNeural Computation
Vol/bind17
Udgave nummer9
Sider (fra-til)1921-1926
Antal sider6
ISSN0899-7667
DOI
StatusUdgivet - sep. 2005
Udgivet eksterntJa

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