Variational Inference over Nonstationary Data Streams for Exponential Family Models

Variational Inference over Nonstationary Data Streams for Exponential Family Models

In many modern data analysis problems, the available data is not static but, instead, comes in a streaming fashion. Performing Bayesian inference on a data stream is challenging for several reasons. First, it requires continuous model updating and the ability to handle a posterior distribution condi...

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Bibliografiske detaljer
Main Authors: Andrés R. Masegosa, Darío Ramos-López, Antonio Salmerón, Helge Langseth, Thomas D. Nielsen
Format: Article
Sprog:English
Udgivet: MDPI AG 2020-11-01
Serier:Mathematics
Fag:
latent variable models
nonstationary data streams
concept drift
variational inference
power priors
exponential forgetting
Online adgang:https://www.mdpi.com/2227-7390/8/11/1942

Internet

https://www.mdpi.com/2227-7390/8/11/1942

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