692f93be8c7a41525c0baf2076aecfb4-Reviews.html

This paper proposes an approach to exact energy minimization in discrete graphical models. The key idea is as follows: The LP relaxation of the problem allows to identify, via arc consistency/weak tree agreement, nodes for which the LP solution is also optimal in the discrete sense. The nodes for which discrete optimality cannot be established from the solution of the LP then define a subproblem, a hopefully small graph, which is solved exactly using a combinatorial solver. One of the contributions of the paper is to show that, if the combinatorial solution's boundary is consistent with the optimal part of the LP solution, the global optimum has been established. If the condition is not met, the combinatorial search area must be grown by the set of variables for which boundary consistency does not hold.