# Variational Bayesian Learning Theory

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- eBook:Variational Bayesian Learning Theory
- Author:Shinichi Nakajima, Kazuho Watanabe, Masashi Sugiyama
- Edition:1 edition
- Categories:
- Data:August 22, 2019
- ISBN:1107076153
- ISBN-13:9781107076150
- Language:English
- Pages:558 pages
- Format:PDF

**Book Description**

**Content**

1. Bayesian Learning

2. Variational Bayesian Learning

Part II - Algorithm

3. VB Algorithm for Multilinear Models

4. VB Algorithm for Latent Variable Models

5. VB Algorithm under No Conjugacy

Part III - Nonasymptotic Theory

6. Global VB Solution of Fully Observed Matrix Factorization

7. Model-Induced Regularization and Sparsity Inducing Mechanism

8. Performance Analysis of VB Matrix Factorization

9. Global Solver for Matrix Factorization

10. Global Solver for Low-Rank Subspace Clustering

11. Efficient Solver for Sparse Additive Matrix Factorization

12. MAP and Partially Bayesian Learning

Part IV - Asymptotic Theory

13. Asymptotic Learning Theory

14. Asymptotic VB Theory of Reduced Rank Regression

15. Asymptotic VB Theory of Mixture Models

16. Asymptotic VB Theory of Other Latent Variable Models

17. Unified Theory for Latent Variable Models

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