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