Em Algorithm, Machine Learning, Data Mining, Jensens Inequality, Bayes Theorem.
will give more than 2 weights, but the previous result can be generalized by induction to many weights. The final concept to understand is the Kullback-Leibler divergence which is a measure of the dissimilarity between two probability distributions q(z) and p(z). The KL-divergence is always greater