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Variational Bayesian methods approximate intractable integrals found in Bayesian inference and machine learning. Primarily, these methods serve one of two purposes: Approximating the posterior distribution, or bounding the marginal likelihood of observed data.

1 vote

Applying variational inference to this model

You derived the variational lower bound in your equation. Have a look at the wiki page for variational approximation. https://en.wikipedia.org/wiki/Variational_Bayesian_methods
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0 votes

Applying variational inference to this model

tried to calculate it without any warranty. $P(y|x\beta,\frac{\sigma}{w_i})P(\beta|\beta_0,\Sigma_0)$ at one point I have $-\beta(zy\sum{x_i }+ \Sigma_0\beta_0)+0.5(z\sum{x_i}+\Sigma_0)\beta^2$ where …
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