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Hidden Conditional Random Fields
October 2007 (vol. 29 no. 10)
pp. 1848-1852
We present a discriminative latent variable model for classification problems in structured domains where inputs can be represented by a graph of local observations. A hidden-state Conditional Random Field framework learns a set of latent variables conditioned on local features. Observations need not be independent and may overlap in space and time.

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Index Terms:
object recognition, model, supervised learning, classification
Citation:
Ariadna Quattoni, Sybor Wang, Louis-Philippe Morency, Michael Collins, Trevor Darrell, "Hidden Conditional Random Fields," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, no. 10, pp. 1848-1852, Oct. 2007, doi:10.1109/TPAMI.2007.1124
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