Partial optimality via iterative pruning for the potts model

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Abstract

We propose a novel method to obtain a part of an optimal non-relaxed integral solution for energy minimization problems with Potts interactions, known also as the minimal partition problem. The method empirically outperforms previous approaches likeMQPBO and Kovtun's method in most of our test instances and especially in hard ones. As a starting point our approach uses the solution of a commonly accepted convex relaxation of the problem. This solution is then iteratively pruned until our criterion for partial optimality is satisfied. Due to its generality our method can employ any solver for the considered relaxed problem. © 2013 Springer-Verlag.

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Swoboda, P., Savchynskyy, B., Kappes, J., & Schnörr, C. (2013). Partial optimality via iterative pruning for the potts model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7893 LNCS, pp. 477–488). https://doi.org/10.1007/978-3-642-38267-3_40

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