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Activity Number: 307 - Bayesian Computational Advances for Complex and Large-Scale Data
Type: Invited
Date/Time: Tuesday, August 1, 2017 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Computing
Abstract #322373 View Presentation
Title: A Variational Bayesian Algorithm for Sparse PCA
Author(s): Feng Liang* and Yunbo Ouyang and Jianjun Hu
Companies: University of Illinois at Urbana Champaign and University of Illinois at Urbana Champaign and Union Bank
Keywords: Variational Bayes ; Bayesian consistency ; Sparse PCA
Abstract:

We propose a Bayesian approach to sparse principal components analysis (PCA). Our algorithm, which is based on variational approximation, can scale with large data size and meanwhile achieves Bayesian consistency when both p and n go to infinity. Empirical studies have demonstrated the competitive performance of the proposed algorithm.


Authors who are presenting talks have a * after their name.

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