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A study of Nesterov's scheme for Lagrangian decomposition and MAP labeling
2011
CVPR 2011
We study the MAP-labeling problem for graphical models by optimizing a dual problem obtained by Lagrangian decomposition. In this paper, we focus specifically on Nesterov's optimal first-order optimization scheme for nonsmooth convex programs, that has been studied for a range of other problems in computer vision and machine learning in recent years. We show that in order to obtain an efficiently convergent iteration, this approach should be augmented with a dynamic estimation of a
doi:10.1109/cvpr.2011.5995652
dblp:conf/cvpr/SavchynskyyKSS11
fatcat:z3fgazxkbzevpbvqbxooheqqie