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[Archimedeans] Bayesian Inference and the Bernstein-von-Mises Theorem

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If you have a question about this talk, please contact Jason Kwong .

In this talk I will discuss the history of a beautiful theorem from mathematical statistics that reconciles these two paradigms from a frequentist point of view: The Bernstein-von Mises phenomenon, which was first discovered by Laplace in a simple case and worked out as a general theorem by mathematicians in the 20th century, states that Bayesian inference based on the posterior distribution is actually `in most cases frequentist optimal’, in a sense I will explain.

This talk is part of the The Archimedeans 2016 series.

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