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The expectation-maximization (EM) algorithm introduced by Dempster et al in 1977 is a very general method to solve maximum likelihood estimation problems.
Maximum likelihood from incomplete data via the EM algorithm
A. P. Dempster, N. M. Laird, and D. B. Rubin · 1977
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Finding the observed information matrix when using the EM algorithm
T. A. Louis · 1982
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The SEM Algorithm: a Probabilistic Teacher Algorithm Derived from the EM Algorithm for the Mixture Problem
G. Celeux and J. Diebolt · 1985
Earlier work this paper cites.
The Calculation of Posterior Distributions by Data Augmentation
M. A. Tanner and W. H. Wong · 1987
Earlier work this paper cites.
A fast improvement of the EM algorithm on its own terms
I. Meilijson · 1989
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A Monte Carlo implementation of the EM algorithm and the poor man’s data augmentation algorithm
G. Wei and M. A. Tanner · 1990
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Elements of Information Theory
T. M. Cover and J. A. Thomas · 1991
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A classification EM algorithm for clustering and two stochastic versions
G. Celeux and G. Govaert · 1992
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Numerical Recipes in C
W. H. Press, B. P. Flannery, S. A. Teukolsky, and W. T. Vetterling · 1992
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Conjugate gradient acceleration of the EM algorithm
M. Jamshidian and R. I. Jennrich · 1993
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Maximum likelihood via the ECM algorithm: a general framework
X. L. Meng and D. B. Rubin · 1993
Cited alongside, same era.
Space-Alternating Generalized Expectation-Maximization Algorithm
J. A. Fessler and A. O. Hero · 1994
Cited alongside, same era.
The ECME algorithm: a simple extension of EM and ECM with faster monotone convergence
C. Liu and D. B. Rubin · 1994
Cited alongside, same era.
On Stochastic Versions of the EM Algorithm
G. Celeux, D. Chauveau, and J. Diebolt · 1995
Cited alongside, same era.
Penalized Maximum-Likelihood Image Reconstruction Using Space-Alternating Generalized EM Algorithms
J. A. Fessler and A. O. Hero · 1995
Cited alongside, same era.
The EM Algorithm: A Guided Tour
C. Couvreur · 1996
Cited alongside, same era.
A view of the EM algorithm that justifies incremental, sparse, and other variants
R. Neal and G. Hinton · 1998
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Convergence of a stochastic approximation version of the EM algorithm
B. Delyon, M. Lavielle, and E. Moulines · 1999
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Parameter Expansion for Data Augmentation
J. S. Liu and Y. N. Wu · 1999
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Seeking efficient data augmentation schemes via conditional and marginal data augmentation
X. L. Meng and D. A. van Dyk · 1999
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Kullback Proximal Algorithms for Maximum Likelihood Estimation
S. Chrétien and A. O. Hero · 2000
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Algorithms based on data augmentation: A graphical representation and comparison
D. A. van Dyk and X. L. Meng · 2000
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The EM Algorithm - An Old Folk Song Sung To A Fast New Tune
X. L. Meng and D. A. van Dyk · 1997
Cited alongside, same era.
Convexity, Maximum Likelihood and All That
A. Berger · 1998
Cited alongside, same era.
A Gentle Tutorial of the EM Algorithm and its Application to Parameter Estimation for Gaussian Mixture and Hidden Markov Models
J. Bilmes · 1998
Cited alongside, same era.
Parameter Expansion to Accelerate EM: The PX-EM Algorithm
C. Liu, D. B. Rubin, and Y. N. Wu · 1998
Cited alongside, same era.
Later among the works it cites.
A Component-wise EM Algorithm for Mixtures
G. Celeux, S. Chrétien, F. Forbes, and A. Mkhadri · 2001
Later among the works it cites.
The Expectation Maximization Algorithm
F. Dellaert · 2002
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Coupling a stochastic approximation version of EM with a MCMC procedure
E. Kuhn and M. Lavielle · 2002
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An Example of Algorithm Mining: Covariance Adjustment to Accelerate EM and Gibbs
C. Liu · 2003
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