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AI/ML Seminar Series: Revisiting Variational Expectation Maximization: Robert Bamler

The AI/ML Seminar Series is proud to present Robert Bamler, Postdoctoral Research, Department of Computer Science, UC Irvine. Bayesian inference is often advertised for applications where posterior uncertainties matter. A less appreciated advantage of Bayesian inference is that it allows for highly scalable model selection ("hyperparameter tuning") via the Expectation Maximization (EM) algorithm and its approximate variant, variational EM. This talk will discuss an application and an improvement of variational EM. 

Monday, October 21, 2019 at 1:00pm to 2:00pm

Donald Bren Hall, 4011
6210 Donald Bren Hall, Irvine, CA 92697

Event Type

Lectures / Presentations, Speakers, Technology


General Public, Students, Postdocs




Information & Computer Sciences


Event Sponsor

Center for Machine Learning and Intelligent Systems

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