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Exact Algorithms for Two Quadratic Euclidean Problems of Searching for the Largest Subset and Longest Subsequence

机译:用于搜索最大子集和最长的两个二次欧几里德问题的精确算法

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The following two strongly NP-hard problems are considered. In the first problem, we need to find in the given finite set of points in Euclidean space the subset of largest size such that the sum of squared distances between the elements of this subset and its unknown centroid (geometrical center) does not exceed a given percentage of the sum of squared distances between the elements of the input set and its centroid. In the second problem, the input is a sequence (not a set) and we have some additional constraints on the indices of the elements of the chosen subsequence under the same restriction on the sum of squared distances as in the first problem. Both problems can be treated as data editing problems aimed to find similar elements and removal of extraneous (dissimilar) elements. We propose exact algorithms for the cases of both problems in which the input points have integer-valued coordinates. If the space dimension is bounded by some constant, our algorithms run in a pseudopolynomial time. Some results of numerical experiments illustrating the performance of the algorithms are presented.
机译:考虑以下两个强烈的难题。在第一个问题中,我们需要在欧几里德空间中的给定有限组点中找到最大尺寸的子集,使得该子集的元素与其未知质心(几何中心)之间的平方距离之和不超过给定的输入集元素与其质心之间的平方距离之和的百分比。在第二个问题中,输入是序列(不是集合),并且我们对所选择的子宫的元素的元素的指数具有一些额外的约束,在与第一个问题中的平方距离之和的相同限制下。这两个问题都可以被视为数据编辑问题,旨在找到类似的元素和去除外来(不同的)元件。我们为输入点具有整数值坐标的两个问题提出了精确的算法。如果空间维度受到某种常量的界限,则我们的算法在伪二极管时间内运行。提出了说明算法性能的数值实验的一些结果。

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