Show that the bound given in Equation 7.6 is maximised (i.e. equal to the true \(\log\) marginal likelihood) when \(Q(\boldsymbol{\theta})\) is identical to the true posterior \(p(\boldsymbol{\theta} \mid \mathbf{X})\).

Data from Equation 7.6

Transcribed Image Text:

log p(Y) = IV log/Q(6) P(Y, 0) Q(0) p(Y, 0) Q(0) log Q(0) -de de = L(Q).