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arXiv 1812.01482cs.CCcs.DScs.SI
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通过顶点覆盖等参数化的目标集选择

Target Set Selection parameterized by vertex cover and more

Suman Banerjee, Rogers Mathew, Fahad Panolan

摘要:

给定一个简单的无向图$G$和一个阈值函数$τ:V(G) \rightarrow \mathbb{N}$,\textsc{Target Set Selection}(TSS)问题是关于选择一个最小基数集,比如说$S \subseteq V(G)$,使得以$S$作为其种子集开始扩散过程最终将导致激活$G$中的所有节点。对于任何非负整数$i$,如果图$G-T$中任何顶点的度最多为$i$,则我们称集合$T\subseteq V(G)$是$G$的“度- $i$调制器”。图的度- $0$调制子就是图的顶点覆盖.考虑一个图$G$,它的顶点和边都是$n$和$m$。我们在TSS问题上有以下结果:-> Nichterlein等人[ Social Network Analysis and Mining,2013]表明,可以在$O(2^{(2^{t}+1)t}\cdot m)$时间内计算最佳大小的目标集,其中$t$表示$G$的最小度- $0$调制器的基数。我们通过设计一个在时间上运行的算法$2^{O(t\log t)}n^{O(1)}$来改进这个结果。->我们设计了一个$2^{2^{O(t)}}n^{O(1)}$时间算法来计算$G$的最优目标集,其中$t$是$G$的最小度$1$调制器的大小。

英文摘要:

Given a simple, undirected graph $G$ with a threshold function $τ:V(G) \rightarrow \mathbb{N}$, the \textsc{Target Set Selection} (TSS) problem is about choosing a minimum cardinality set, say $S \subseteq V(G)$, such that starting a diffusion process with $S$ as its seed set will eventually result in activating all the nodes in $G$. For any non-negative integer $i$, we say a set $T\subseteq V(G)$ is a "degree-$i$ modulator" of $G$ if the degree of any vertex in the graph $G-T$ is at most $i$. Degree-$0$ modulators of a graph are precisely its vertex covers. Consider a graph $G$ on $n$ vertices and $m$ edges. We have the following results on the TSS problem: -> It was shown by Nichterlein et al. [Social Network Analysis and Mining, 2013] that it is possible to compute an optimal-sized target set in $O(2^{(2^{t}+1)t}\cdot m)$ time, where $t$ denotes the cardinality of a minimum degree-$0$ modulator of $G$. We improve this result by designing an algorithm running in time $2^{O(t\log t)}n^{O(1)}$. -> We design a $2^{2^{O(t)}}n^{O(1)}$ time algorithm to compute an optimal target set for $G$, where $t$ is the size of a minimum degree-$1$ modulator of $G$.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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