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

机译:搜索最大子集和最长子序列的两个二次欧式问题的精确算法

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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NP难题。在第一个问题中,我们需要在给定的欧几里得空间中的有限点集中找到最大大小的子集,以使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值输入集的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,输入是一个序列(不是集合),并且在与第一个问题相同的平方距离总和约束下,对所选子序列元素的索引具有一些附加约束。这两个问题都可以看作是数据编辑问题,旨在查找相似的元素并删除无关的元素。对于输入点具有整数值坐标的两个问题,我们提出了精确的算法。如果空间维数受某个常数限制,则我们的算法将在伪多项式时间内运行。数值实验的一些结果说明了算法的性能。

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