Memorized Variational Continual Learning for Dirichlet Process Mixtures

Memorized Variational Continual Learning for Dirichlet Process Mixtures

Bayesian nonparametric models are theoretically suitable for streaming data due to their ability to adapt model complexity with the observed data. However, very limited work has addressed posterior inference in a streaming fashion, and most of the existing variational inference algorithms require tr...

Full description

Bibliographic Details
Main Authors: Yang Yang, Bo Chen, Hongwei Liu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Bayesian nonparametric
streaming data
variational continual learning
Dirichlet process mixture
memorized sufficient statistics
discrete and real-valued datasets
Online Access:https://ieeexplore.ieee.org/document/8871157/

Internet

https://ieeexplore.ieee.org/document/8871157/

Similar Items