Em Algorithm, Machine Learning, Data Mining, Jensens Inequality, Bayes Theorem.
in terms of the distribution q(z). The inequality gives a lower bound on the log-likelihood. The difference between the log-likelihood and L(q, θ) can be seen to be the KL-divergence between q(z) and p(Z|X, θ ). The expansion of p(X,Z| θ) = P(Z|X, θ)P(X| θ) is used to prove this. There is exact