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首页> 外文期刊>Inverse Problems: An International Journal of Inverse Problems, Inverse Methods and Computerised Inversion of Data >Generalized Bregman distances and convergence rates for non-convex regularization methods
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Generalized Bregman distances and convergence rates for non-convex regularization methods

机译:非凸正则化方法的广义Bregman距离和收敛速度

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摘要

We generalize the notion of Bregman distance using concepts from abstract convexity in order to derive convergence rates for Tikhonov regularization with non-convex regularization terms. In particular, we study the non-convex regularization of linear operator equations on Hilbert spaces, showing that the conditions required for the application of the convergence rates results are strongly related to the standard range conditions from the convex case. Moreover, we consider the setting of sparse regularization, where we show that a rate of order δ~(1/p) holds, if the regularization term has a slightly faster growth at zero than |t|~p.
机译:我们使用抽象凸度的概念来概括Bregman距离的概念,以得出带有非凸正则化项的Tikhonov正则化的收敛速度。特别是,我们研究了希尔伯特空间上线性算子方程的非凸正则化,表明应用收敛速率结果所需的条件与凸情况下的标准范围条件密切相关。此外,我们考虑稀疏正则化的设置,如果正则化项在零处的增长比| t |〜p快一点,则表明保持δ〜(1 / p)的速率。

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