2017
Dynamic Importance Sampling for Anytime Bounds of the Partition Function
NeurIPS 2017poster
Computing the partition function is a key inference task in many graphical models. In this paper, we propose a dynamic importance sampling scheme that provides anytime finite-sample bounds for the partition function. Our algorithm balances the advantages of the three major inference strategies, heu…