We present a dual decomposition approach to the treereweighted belief propagation objective. Each tree in the tree-reweighted bound yields one subproblem, which can be solved with...
We show that various duals that occur in optimization and constraint satisfaction can be classified as inference duals, relaxation duals, or both. We discuss linear programming, su...
Combining information from the higher level and the lower level has long been recognized as an essential component in holistic image understanding. However, an efficient inferenc...
Approximate MAP inference in graphical models is an important and challenging problem for many domains including computer vision, computational biology and natural language unders...
We present a novel dual decomposition approach to MAP inference with highly connected discrete graphical models. Decompositions into cyclic k-fan structured subproblems are shown t...