Principled Parallel Mean-Field Inference for Discrete Random Fields
Principled Parallel Mean-Field Inference for Discrete Random Fields
Mean-field variational inference is one of the most popular approaches to inference in discrete random fields. Standard mean-field optimization is based on coordinate descent and in many situations can be impractical. Thus, in practice, various parallel techniques are used, which either rely on ad hoc smoothing with heuristically set parameters, …