Convergence analysis of a proximal point algorithm for minimizing differences of functions |
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Authors: | Nguyen Thai An |
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Institution: | Institute of Research and Development, Duy Tan University, Da Nang, Vietnam. |
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Abstract: | Several optimization schemes have been known for convex optimization problems. However, numerical algorithms for solving nonconvex optimization problems are still underdeveloped. A significant progress to go beyond convexity was made by considering the class of functions representable as differences of convex functions. In this paper, we introduce a generalized proximal point algorithm to minimize the difference of a nonconvex function and a convex function. We also study convergence results of this algorithm under the main assumption that the objective function satisfies the Kurdyka–?ojasiewicz property. |
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Keywords: | DC programming proximal point algorithm difference of convex functions Kurdyka–?ojasiewicz inequality |
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