I recently read paper by Chong Wang and David M. Blei "Variational Inference for the Nested Chinese Restaurant Process". And I couldn't understand the next part (from p.5):
The variational update functions for W and x depend on the actual distributions we use, and deriving them is straightforward. If they include an infinite sum then we apply similar techniques as we did for q(vi).
Could anyone explain (and give an example) how to implement variational update for W and x?
And if there are any other good papers/tutorials/code to understand variational inference for hLDA?
Thanks for any suggestions.