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Fast Distance Multiplication of Unit-Monge Matrices

机译:单位维数矩阵的快速距离乘法

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Monge matrices play a fundamental role in optimisation theory, graph and string algorithms. Distance multiplication of two Monge matrices of size n can be performed in time O(n (2)). Motivated by applications to string algorithms, we introduced in previous works a subclass of Monge matrices, that we call simple unit-Monge matrices. We also gave a distance multiplication algorithm for such matrices, running in time O(n (1.5)). Landau asked whether this problem can be solved in linear time. In the current work, we give an algorithm running in time O(nlogn), thus approaching an answer to Landau's question within a logarithmic factor. The new algorithm implies immediate improvements in running time for a number of algorithms on strings and graphs. In particular, we obtain an algorithm for finding a maximum clique in a circle graph in time O(nlog(2) n), and a surprisingly efficient algorithm for comparing compressed strings. We also point to potential applications in group theory, by making a connection between unit-Monge matrices and Coxeter monoids. We conclude that unit-Monge matrices are a fascinating object and a powerful tool, that deserve further study from both the mathematical and the algorithmic viewpoints.
机译:Monge矩阵在优化理论,图形和字符串算法中起着基本作用。可以在时间O(n(2))中执行大小为n的两个Monge矩阵的距离乘法。受字符串算法应用程序的启发,我们在以前的工作中介绍了Monge矩阵的子类,我们将其称为简单单位Monge矩阵。我们还为此类矩阵提供了距离乘法算法,并在时间O(n(1.5))中运行。兰道问这个问题是否可以在线性时间内解决。在当前的工作中,我们给出了一种在时间O(nlogn)上运行的算法,从而在对数因子内找到了Landau问题的答案。新算法意味着字符串和图形上许多算法的运行时间会立即得到改善。特别是,我们获得了一种算法,用于在时间O(nlog(2)n)中找到圆形图中的最大集团,并获得了一种令人惊讶的高效算法,用于比较压缩字符串。通过在单位蒙格矩阵和Coxeter单面体之间建立联系,我们还指出了组理论中的潜在应用。我们得出结论,单位Monge矩阵是一个有趣的对象和强大的工具,值得从数学和算法的角度进行进一步研究。

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