Zhengshan Dong

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This paper proposes a new customized proximal point algorithm for linearly constrained convex optimization problem, and further extends the proposed method to separable convex optimization problem with linear constraints. The global convergence and a worst-case convergence rate of the proposed methods are proven under some mild assumptions. Preliminary(More)
In this paper, two homotopy methods, which combine the advantage of the ho-motopy technique with the effectiveness of the iterative hard thresholding method, are presented for solving the compressed sensing problem. Under some mild assumptions , we prove that the limits of the sequences generated by the proposed homotopy methods are feasible solutions of(More)
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