半径约束下矩阵补全的参数化算法

Tomohiro Koana, Vincent Froese, R. Niedermeier
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引用次数: 9

摘要

考虑缺少条目的矩阵,我们研究了NP-hard矩阵补全问题,其中得到的补全矩阵必须有有限的(局部)半径。在纯半径版本中,这意味着目标是填充条目,使得存在一个“中心字符串”,其与所有矩阵行的汉明距离尽可能小。在字符串学中,这个问题也被称为带通配符的最接近字符串。在本地半径版本中,请求的中心字符串必须是已完成矩阵的其中一行。Hermelin和Rozenberg [CPM 2014, TCS 2016]对带通配符的最接近字符串进行了参数化复杂性研究。我们回答了他们的一个开放问题,修复了他们工作中关于固定参数可跟踪性结果的错误,并改进了一些运行时间上限。对于局部半径情况,我们揭示了一种计算复杂度二分法。一般来说,我们的结果表明,尽管也是NP-hard,但这种变体通常允许更快的(固定参数)算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parameterized Algorithms for Matrix Completion With Radius Constraints
Considering matrices with missing entries, we study NP-hard matrix completion problems where the resulting completed matrix shall have limited (local) radius. In the pure radius version, this means that the goal is to fill in the entries such that there exists a 'center string' which has Hamming distance to all matrix rows as small as possible. In stringology, this problem is also known as Closest String with Wildcards. In the local radius version, the requested center string must be one of the rows of the completed matrix. Hermelin and Rozenberg [CPM 2014, TCS 2016] performed parameterized complexity studies for Closest String with Wildcards. We answer one of their open questions, fix a bug concerning a fixed-parameter tractability result in their work, and improve some upper running time bounds. For the local radius case, we reveal a computational complexity dichotomy. In general, our results indicate that, although being NP-hard as well, this variant often allows for faster (fixed-parameter) algorithms.
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