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Adaptive variational Bayes: Optimality, computation and applications
March 12, 2024, 4:45 a.m. | Ilsang Ohn, Lizhen Lin
stat.ML updates on arXiv.org arxiv.org
Abstract: In this paper, we explore adaptive inference based on variational Bayes. Although several studies have been conducted to analyze the contraction properties of variational posteriors, there is still a lack of a general and computationally tractable variational Bayes method that performs adaptive inference. To fill this gap, we propose a novel adaptive variational Bayes framework, which can operate on a collection of models. The proposed framework first computes a variational posterior over each individual model …
abstract analyze applications arxiv bayes computation explore gap general inference math.st paper stat.ml stat.th studies tractable type
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