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Sub-Gaussian Concentration and Entropic Normality of the Maximum Likelihood Estimator
It is well known that, under standard regularity conditions, the maximum likelihood estimator (MLE) satisfies a central limit theorem and converges in distribution to a Gaussian random variable as the sample size grows. This paper strengthens this classical result by developing several stronger form
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