{"title":"k-比克形问题的参数化复杂度","authors":"Bingkai Lin","doi":"10.1145/3212622","DOIUrl":null,"url":null,"abstract":"Given a graph G and an integer k, the k-Biclique problem asks whether G contains a complete bipartite subgraph with k vertices on each side. Whether there is an f(k) ċ |G|O(1)-time algorithm, solving k-Biclique for some computable function f has been a longstanding open problem. We show that k-Biclique is W[1]-hard, which implies that such an f(k) ċ |G|O(1)-time algorithm does not exist under the hypothesis W[1] ≠ FPT from parameterized complexity theory. To prove this result, we give a reduction which, for every n-vertex graph G and small integer k, constructs a bipartite graph H = (L⊍ R,E) in time polynomial in n such that if G contains a clique with k vertices, then there are k(k − 1)/2 vertices in L with nθ(1/k) common neighbors; otherwise, any k(k − 1)/2 vertices in L have at most (k+1)! common neighbors. An additional feature of this reduction is that it creates a gap on the right side of the biclique. Such a gap might have further applications in proving hardness of approximation results. Assuming a randomized version of Exponential Time Hypothesis, we establish an f(k) ċ |G|o(√k)-time lower bound for k-Biclique for any computable function f. Combining our result with the work of Bulatov and Marx [2014], we obtain a dichotomy classification of the parameterized complexity of cardinality constraint satisfaction problems.","PeriodicalId":17199,"journal":{"name":"Journal of the ACM (JACM)","volume":"1 1","pages":"1 - 23"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"36","resultStr":"{\"title\":\"The Parameterized Complexity of the k-Biclique Problem\",\"authors\":\"Bingkai Lin\",\"doi\":\"10.1145/3212622\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Given a graph G and an integer k, the k-Biclique problem asks whether G contains a complete bipartite subgraph with k vertices on each side. Whether there is an f(k) ċ |G|O(1)-time algorithm, solving k-Biclique for some computable function f has been a longstanding open problem. We show that k-Biclique is W[1]-hard, which implies that such an f(k) ċ |G|O(1)-time algorithm does not exist under the hypothesis W[1] ≠ FPT from parameterized complexity theory. To prove this result, we give a reduction which, for every n-vertex graph G and small integer k, constructs a bipartite graph H = (L⊍ R,E) in time polynomial in n such that if G contains a clique with k vertices, then there are k(k − 1)/2 vertices in L with nθ(1/k) common neighbors; otherwise, any k(k − 1)/2 vertices in L have at most (k+1)! common neighbors. An additional feature of this reduction is that it creates a gap on the right side of the biclique. Such a gap might have further applications in proving hardness of approximation results. Assuming a randomized version of Exponential Time Hypothesis, we establish an f(k) ċ |G|o(√k)-time lower bound for k-Biclique for any computable function f. Combining our result with the work of Bulatov and Marx [2014], we obtain a dichotomy classification of the parameterized complexity of cardinality constraint satisfaction problems.\",\"PeriodicalId\":17199,\"journal\":{\"name\":\"Journal of the ACM (JACM)\",\"volume\":\"1 1\",\"pages\":\"1 - 23\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-08-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"36\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the ACM (JACM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3212622\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the ACM (JACM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3212622","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 36
摘要
给定一个图G和一个整数k, k- biclique问题问的是G是否包含一个每边有k个顶点的完全二部子图。是否有一个f (k)ċ| | G O(1)算法,解决k-Biclique对于一些可计算函数f是一个长期的开放问题。我们从参数化复杂性理论证明了k- biclique是W[1]-hard的,这意味着在W[1]≠FPT的假设下,f(k) * |G|O(1)时间算法不存在。为了证明这一结果,我们给出了一个约简,对于每一个n顶点图G和小整数k,在n的时间多项式上构造一个二部图H = (L R,E),使得如果G包含有k个顶点的团,则L中有k(k−1)/2个顶点具有nθ(1/k)个共邻;否则,L中的任何k(k−1)/2个顶点最多有(k+1)!常见的邻居。这种减少的另一个特点是,它在自行车的右侧产生一个间隙。这种差距可能在证明近似结果的硬度方面有进一步的应用。假设随机版本的指数时间的假设,我们建立一个f (k)ċ| | G o(√k) -下界为k-Biclique任何可计算函数f。将我们的结果与Bulatov和马克思的工作[2014],我们获得一个二分法分类的参数化基数约束满足问题的复杂性。
The Parameterized Complexity of the k-Biclique Problem
Given a graph G and an integer k, the k-Biclique problem asks whether G contains a complete bipartite subgraph with k vertices on each side. Whether there is an f(k) ċ |G|O(1)-time algorithm, solving k-Biclique for some computable function f has been a longstanding open problem. We show that k-Biclique is W[1]-hard, which implies that such an f(k) ċ |G|O(1)-time algorithm does not exist under the hypothesis W[1] ≠ FPT from parameterized complexity theory. To prove this result, we give a reduction which, for every n-vertex graph G and small integer k, constructs a bipartite graph H = (L⊍ R,E) in time polynomial in n such that if G contains a clique with k vertices, then there are k(k − 1)/2 vertices in L with nθ(1/k) common neighbors; otherwise, any k(k − 1)/2 vertices in L have at most (k+1)! common neighbors. An additional feature of this reduction is that it creates a gap on the right side of the biclique. Such a gap might have further applications in proving hardness of approximation results. Assuming a randomized version of Exponential Time Hypothesis, we establish an f(k) ċ |G|o(√k)-time lower bound for k-Biclique for any computable function f. Combining our result with the work of Bulatov and Marx [2014], we obtain a dichotomy classification of the parameterized complexity of cardinality constraint satisfaction problems.