Generalized interpretation of optimization methods for labeling problems

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Various combinatorial optimization methods have been considered independently. The purpose of this study is to organize theoretically those optimization methods, which differ by their natures, and to indicate clearly what are common and what are different among those methods. The authors deal with a labeling problem in the optimization methods and propose a generalized algorithm to solve the problem. They show that the algorithm can derive the conventional optimization methods, such as the relaxation matching method, neural networks, and the dynamic programming matching method. >

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