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The Expectation-Maximization (EM) algorithm is an iterative method to maximize the log-likelihood function for parameter estimation.
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Boyles, R.A., 1983. On the convergence of the EM algorithm . Journal of the Royal Statistical Society. Series B (Methodological), pp.47-50
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Wu, C.F.J. 1983, On the Convergence Properties of the EM Algorithm , The Annals of Statistics, vol. 11, no. 1, pp. 95-103
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Redner, R.A., Walker, H.F. Mixture Densities, Maximum-Likelihood and the EM Algorithm, SIAM Review, Vol. 26, No.2, April 1984, pp. 195-239
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Meng, X.L. and Rubin, D.B., 1993. Maximum likelihood estimation via the ECM algorithm: A general framework . Biometrika, 80(2), pp.267-278
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Meng, X. and Rubin, D.B. 1994, On the global and componentwise rates of convergence of the EM algorithm , Linear Algebra and Its Applications, vol. 199, no. 1, pp. 413-425
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Dasgupta, S. and Schulman, L. J. A probabilistic analysis of EM for mixtures of separated, spherical gaussians . Journal of Machine Learning Research, 8:203–226, 2007
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Chrétien, S. and Hero, A. O. On EM algorithms and their proximal generalizations . ESAIM: Probability and Statistics, 12:308–326, 2008
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McLachlan, G.J. and Krishnan, T. 2008, The EM algorithm and extensions , 2nd edn, Wiley-Interscience, Hoboken, N.J
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Talagrand, M., 1996. A new look at independence . The Annals of probability, pp.1-34
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Liu, C., Rubin, D.B. and Wu, Y.N., 1998. Parameter expansion to accelerate EM: The PX-EM algorithm . Biometrika, pp.755-770
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Ledoux, M. and Talagrand, M., 2013. Probability in Banach Spaces: isoperimetry and processes . Springer Science & Business Media
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Wang, Z., Gu, Q., Ning, Y. and Liu, H., 2015. High dimensional em algorithm: Statistical optimization and asymptotic normality . In Advances in Neural Information Processing Systems (pp. 2521-2529)
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2015
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Balakrishnan, S., Wainwright, M.J. and Yu, B., 2017. Statistical guarantees for the EM algorithm: From population to sample-based analysis . The Annals of Statistics, 45(1), pp.77-120
2017
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