Scalable Model Selection for Belief Networks

Zhao Song, Yusuke Muraoka, Ryohei Fujimaki, Lawrence Carin

Nov-21-2025, 12:12:57 GMT–Neural Information Processing Systems

The factorized asymptotic Bayesian ( FAB) approach has recently been shown as a scalable model-selection framework for latent variable models.

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Neural Information Processing Systems

Nov-21-2025, 12:12:57 GMT

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Country:
- Asia > Middle East
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- Europe > United Kingdom
  - England > Cambridgeshire > Cambridge (0.04)
- North America > United States
  - California
    - Los Angeles County > Long Beach (0.04)
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  - North Carolina > Durham County
    - Durham (0.04)

Genre:
- Research Report (0.46)

Technology:
- Information Technology > Artificial Intelligence > Machine Learning
  - Learning Graphical Models
    - Directed Networks > Bayesian Learning (0.84)
    - Undirected Networks > Markov Models (0.68)
  - Neural Networks > Deep Learning (1.00)
  - Statistical Learning (1.00)

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Scalable Model Selection for Belief Networks
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