Statistics Seminar: Randomization Posteriors and Generalized Bayesian Inference
Presenter: Edric Tam, Warren Alpert Fellow in AI and Computational Biology, Department of Biomedical Data Science, Stanford University Description: A longstanding question in Bayesian analysis concerns the role of randomization. We introduce randomization posteriors, a class of generalized Bayesian updates obtained by averaging over an auxiliary randomization law. A particularly relevant instance assigns random weights […]