An Analysis of Convex Relaxations for MAP Estimation

Mudigonda, Pawan, Kolmogorov, Vladimir, Torr, Philip

Neural Information Processing Systems 

The problem of obtaining the maximum a posteriori estimate of a general discrete random field (i.e. a random field defined using a finite and discrete set of labels) is known to be

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