Structured Ensemble Cascades
This method as proposed by Weiss et al, NIPS 2010
This page is reserved for a write up by Dan Howarth
Contents
Citation
Sidestepping Intractable Inference with Structured Ensemble Cascades. David Weiss, Benjamin Sapp, and Ben Taskar. Neural Information Processing Systems (NIPS), December 2010.
Online version
Summary
This work introduces a method for intractable inference by "sidestepping" the inference all together by learning a group of sub-models in a structured prediction cascade. For instance, inference on loopy graphical models is intractable. This method overcomes this intractability by splitting the model up into submodels that are loop-less. This builds on the authors previous work of structured prediction cascades where intractable models are learned by learning increasingly complex models while also progressively pruning the set of possible outputs. See structured prediction cascades for an more information about this method.
