# Overdispersed Black-Box Variational Inference

This UAI paper by Ruiz, Titsias and Blei presents important insights for the idea of a black box procedure for VI (which I discussed here). The setup of BBVI is the following: given a target/posterior $\pi$ and a parametric approximation $q_\lambda$, we want to find

$\mathrm{argmin}_\lambda \int \log \left ( \frac{\pi(x)}{q_\lambda(x)} \right ) q_\lambda(x) \mathrm{d}x$

which can be achieved for any $q_\lambda$ by estimating the gradient

$\nabla_\lambda \int \log \left ( \frac{\pi(x)}{q_\lambda(x)} \right ) q_\lambda(x) \mathrm{d}x$

with Monte Carlo Samples and stochastic gradient descent. This works if we can easily sample from $q_\lambda$  and can compute its derivative wrt $\lambda$ in closed form. In the original paper, the authors suggested the use of the score function as a control variate and a Rao-Blackwellization. Both where described in a way that utterly confused me – until now, because Ruiz, Titsias and Blei manage to describe the concrete application of both control variates and Rao-Blackwellization in a very transparent way. Their own contribution to variance reduction (minus some tricks they applied) is based on the fact that the optimal sampling distribution for estimating $\nabla_\lambda \int \log \left ( \frac{\pi(x)}{q_\lambda(x)} \right ) q_\lambda(x) \mathrm{d}x$ is proportional to $\left | \log \left ( \frac{\pi(x)}{q_\lambda(x)} \right ) \right | q_\lambda(x)$ rather than exactly $q_\lambda(x)$. They argue that this optimal sampling distribution is considerably heavier tailed than $q_\lambda(x)$. Their reasoning is mainly that the norm of the gradient (which is essentially $(\nabla_\lambda q_\lambda) \log \left ( \frac{\pi(x)}{q_\lambda(x)} \right ) = q_\lambda(x)(\nabla_\lambda \log q_\lambda(x)) \log \left ( \frac{\pi(x)}{q_\lambda(x)} \right )$)  vanishes for the modes, making that region irrelevant for gradient estimation. The same should be true for the tails of the distribution I think. Overall very interesting work that I strongly recommend reading, if only to understand the original Blackbox VI proposal.