2016
Exponential Stochastic Cellular Automata for Massively Parallel Inference
AISTATS 2016poster
We propose an embarrassingly parallel, memory efficient inference algorithm for latent variable models in which the complete data likelihood is in the exponential family. The algorithm is a stochastic cellular automaton and converges to a valid maximum a posteriori fixed point. Applied to latent Dir…