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首页> 外文期刊>Journal of combinatorial optimization >An accelerated continuous greedy algorithm for maximizing strong submodular functions
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An accelerated continuous greedy algorithm for maximizing strong submodular functions

机译:加速连续贪婪算法以最大化强子模函数

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摘要

An accelerated continuous greedy algorithm is proposed for maximization of a special class of non-decreasing submodular functions subject to a matroid constraint with a approximation for any , where is the curvature with respect to the optimum. Functions in the special class of submodular functions satisfy the criterion , . As an alternative to the standard continuous greedy algorithm, the proposed algorithm can substantially reduce the computational expense by removing redundant computational steps and, therefore, is able to efficiently handle the maximization problems for this special class of submodular functions. Examples of such functions are presented.
机译:提出了一种加速连续贪婪算法,该算法用于最大化受拟阵约束的特殊类别的非递减子模函数,其中任意一个近似,其中曲率相对于最优值。特殊的次模函数类中的函数满足准则,。作为标准连续贪婪算法的替代方法,该算法可通过消除多余的计算步骤来显着减少计算费用,因此能够有效处理此类特殊的子模函数的最大化问题。提供了此类功能的示例。

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