Difference between revisions of "Structured Ensemble Cascades"
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== Summary == | == 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]. 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. | |
== Brief description of the method == | == Brief description of the method == | ||
Revision as of 20:09, 5 October 2011
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]. 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.
