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Expectation Maximization (EM) is among the most popular algorithms for estimating parameters of statistical models.
On the mathematical foundations of theoretical statistics
R. A. Fisher · 1922
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Some methods for classification and analysis of multivariate observations
J. B. MacQueen · 1967
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Maximum-likelihood from incomplete data via the EM algorithm
A. P. Dempster, N. M. Laird, and D. B. Rubin · 1977
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Least squares quantization in PCM
S. P. Lloyd · 1982
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On the convergence properties of the EM algorithm
C. F. J. Wu · 1983
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Mixture densities, maximum likelihood and the EM algorithm
R. A. Redner and H. F. Walker · 1984
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Expected maximum log likelihood estimation
D. Conniffe · 1987
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Statistical mechanics of the maximum-likelihood density estimation
N. Barkai and H. Sompolinsky · 1994
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On convergence properties of the EM algorithm for Gaussian mixtures
L. Xu and M. I. Jordan · 1996
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Learning mixutres of Gaussians
S. Dasgupta · 1999
Cited alongside, same era.
An analysis of the EM algorithm and entropy-like proximal point methods
P. Tseng · 2004
Cited alongside, same era.
A spectral algorithm for learning mixtures models
S. Vempala and G. Wang · 2004
Cited alongside, same era.
On spectral learning of mixtures of distributions
D. Achlioptas and F. McSherry · 2005
Cited alongside, same era.
Learning mixtures of separated nonspherical Gaussians
S. Arora and R. Kannan · 2005
Cited alongside, same era.
A probabilistic analysis of EM for mixtures of separated, spherical Gaussians
S. Dasgupta and L. Schulman · 2007
Cited alongside, same era.
The spectral method for general mixture models
R. Kannan, H. Salmasian, and S. Vempala · 2008
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Polynomial learning of distribution families
M. Belkin and K. Sinha · 2010
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Efficiently learning mixtures of two Gaussians
A. T. Kalai, A. Moitra, and G. Valiant · 2010
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Settling the polynomial learnability of mixtures of Gaussians
A. Moitra and G. Valiant · 2010
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Oracle inequalities in empirical risk minimization and sparse recovery problems
V. Koltchinskii · 2011
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Learning mixtures of spherical Gaussians: moment methods and spectral decompositions
D. Hsu and S. M. Kakade · 2013
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S. C. Brubaker and S. Vempala · 2008
Cited alongside, same era.
Learning mixtures of product distributions using correlations and independence
K. Chaudhuri and S. Rao · 2008
Cited alongside, same era.
On EM algorithms and their proximal generalizations
S. Chrétien and A. O. Hero · 2008
Cited alongside, same era.
Multi-view clustering via canonical correlation analysis
K. Chaudhuri, S. M. Kakade, K. Livescu, and K. Sridharan
Cited in the paper.
Learning mixtures of gaussians using the k-means algorithm
K. Chaudhuri, S. Dasgupta, and A. Vattani
Cited in the paper.
Contributions to the mathematical theory of evolution
K. Pearson
Cited in the paper.
Statistical guarantees for the EM algorithm: From population to sample-based analysis
S. Balakrishnan, M. J. Wainwright, and B. Yu · 2014
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Tight bounds for learning a mixture of two gaussians
M. Hardt and E. Price · 2015
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