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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
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 …