Variational Learning for the Inverted Beta-Liouville Mixture Model and Its Application to Text Categorization

Variational Learning for the Inverted Beta-Liouville Mixture Model and Its Application to Text Categorization

The finite invert Beta-Liouville mixture model (IBLMM) has recently gained some attention due to its positive data modeling capability. Under the conventional variational inference (VI) framework, the analytically tractable solution to the optimization of the variational posterior distribution canno...

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Bibliographic Details
Main Authors: Yongfa Ling, Wenbo Guan, Qiang Ruan, Heping Song, Yuping Lai
Format: Article
Language:English
Published: Universidad Internacional de La Rioja (UNIR) 2022-09-01
Series:International Journal of Interactive Multimedia and Artificial Intelligence
Subjects:
bayesian inference
extended variational inference
mixture model
text categorization
inverted beta-liouville distribution
Online Access:https://www.ijimai.org/journal/bibcite/reference/3157

Internet

https://www.ijimai.org/journal/bibcite/reference/3157

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