907 research outputs found

    Tight Kernel Bounds for Problems on Graphs with Small Degeneracy

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    In this paper we consider kernelization for problems on d-degenerate graphs, i.e. graphs such that any subgraph contains a vertex of degree at most dd. This graph class generalizes many classes of graphs for which effective kernelization is known to exist, e.g. planar graphs, H-minor free graphs, and H-topological-minor free graphs. We show that for several natural problems on d-degenerate graphs the best known kernelization upper bounds are essentially tight.Comment: Full version of ESA 201

    Kernels for Below-Upper-Bound Parameterizations of the Hitting Set and Directed Dominating Set Problems

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    In the {\sc Hitting Set} problem, we are given a collection F\cal F of subsets of a ground set VV and an integer pp, and asked whether VV has a pp-element subset that intersects each set in F\cal F. We consider two parameterizations of {\sc Hitting Set} below tight upper bounds: p=mkp=m-k and p=nkp=n-k. In both cases kk is the parameter. We prove that the first parameterization is fixed-parameter tractable, but has no polynomial kernel unless coNP\subseteqNP/poly. The second parameterization is W[1]-complete, but the introduction of an additional parameter, the degeneracy of the hypergraph H=(V,F)H=(V,{\cal F}), makes the problem not only fixed-parameter tractable, but also one with a linear kernel. Here the degeneracy of H=(V,F)H=(V,{\cal F}) is the minimum integer dd such that for each XVX\subset V the hypergraph with vertex set VXV\setminus X and edge set containing all edges of F\cal F without vertices in XX, has a vertex of degree at most d.d. In {\sc Nonblocker} ({\sc Directed Nonblocker}), we are given an undirected graph (a directed graph) GG on nn vertices and an integer kk, and asked whether GG has a set XX of nkn-k vertices such that for each vertex y∉Xy\not\in X there is an edge (arc) from a vertex in XX to yy. {\sc Nonblocker} can be viewed as a special case of {\sc Directed Nonblocker} (replace an undirected graph by a symmetric digraph). Dehne et al. (Proc. SOFSEM 2006) proved that {\sc Nonblocker} has a linear-order kernel. We obtain a linear-order kernel for {\sc Directed Nonblocker}

    Exploiting c\mathbf{c}-Closure in Kernelization Algorithms for Graph Problems

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    A graph is c-closed if every pair of vertices with at least c common neighbors is adjacent. The c-closure of a graph G is the smallest number such that G is c-closed. Fox et al. [ICALP '18] defined c-closure and investigated it in the context of clique enumeration. We show that c-closure can be applied in kernelization algorithms for several classic graph problems. We show that Dominating Set admits a kernel of size k^O(c), that Induced Matching admits a kernel with O(c^7*k^8) vertices, and that Irredundant Set admits a kernel with O(c^(5/2)*k^3) vertices. Our kernelization exploits the fact that c-closed graphs have polynomially-bounded Ramsey numbers, as we show

    Essentially Tight Kernels For (Weakly) Closed Graphs

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    We study kernelization of classic hard graph problems when the input graphs fulfill triadic closure properties. More precisely, we consider the recently introduced parameters closure number cc and the weak closure number γ\gamma [Fox et al., SICOMP 2020] in addition to the standard parameter solution size kk. For Capacitated Vertex Cover, Connected Vertex Cover, and Induced Matching we obtain the first kernels of size kO(γ)k^{\mathcal{O}(\gamma)} and (γk)O(γ)(\gamma k)^{\mathcal{O}(\gamma)}, respectively, thus extending previous kernelization results on degenerate graphs. The kernels are essentially tight, since these problems are unlikely to admit kernels of size ko(γ)k^{o(\gamma)} by previous results on their kernelization complexity in degenerate graphs [Cygan et al., ACM TALG 2017]. In addition, we provide lower bounds for the kernelization of Independent Set on graphs with constant closure number~cc and kernels for Dominating Set on weakly closed split graphs and weakly closed bipartite graphs

    Point Line Cover: The Easy Kernel is Essentially Tight

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    The input to the NP-hard Point Line Cover problem (PLC) consists of a set PP of nn points on the plane and a positive integer kk, and the question is whether there exists a set of at most kk lines which pass through all points in PP. A simple polynomial-time reduction reduces any input to one with at most k2k^2 points. We show that this is essentially tight under standard assumptions. More precisely, unless the polynomial hierarchy collapses to its third level, there is no polynomial-time algorithm that reduces every instance (P,k)(P,k) of PLC to an equivalent instance with O(k2ϵ)O(k^{2-\epsilon}) points, for any ϵ>0\epsilon>0. This answers, in the negative, an open problem posed by Lokshtanov (PhD Thesis, 2009). Our proof uses the machinery for deriving lower bounds on the size of kernels developed by Dell and van Melkebeek (STOC 2010). It has two main ingredients: We first show, by reduction from Vertex Cover, that PLC---conditionally---has no kernel of total size O(k2ϵ)O(k^{2-\epsilon}) bits. This does not directly imply the claimed lower bound on the number of points, since the best known polynomial-time encoding of a PLC instance with nn points requires ω(n2)\omega(n^{2}) bits. To get around this we build on work of Goodman et al. (STOC 1989) and devise an oracle communication protocol of cost O(nlogn)O(n\log n) for PLC; its main building block is a bound of O(nO(n))O(n^{O(n)}) for the order types of nn points that are not necessarily in general position, and an explicit algorithm that enumerates all possible order types of n points. This protocol and the lower bound on total size together yield the stated lower bound on the number of points. While a number of essentially tight polynomial lower bounds on total sizes of kernels are known, our result is---to the best of our knowledge---the first to show a nontrivial lower bound for structural/secondary parameters

    Covering Many (Or Few) Edges with k Vertices in Sparse Graphs

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    We study the following two fixed-cardinality optimization problems (a maximization and a minimization variant). For a fixed ? between zero and one we are given a graph and two numbers k ? ? and t ? ?. The task is to find a vertex subset S of exactly k vertices that has value at least (resp. at most for minimization) t. Here, the value of a vertex set computes as ? times the number of edges with exactly one endpoint in S plus 1-? times the number of edges with both endpoints in S. These two problems generalize many prominent graph problems, such as Densest k-Subgraph, Sparsest k-Subgraph, Partial Vertex Cover, and Max (k,n-k)-Cut. In this work, we complete the picture of their parameterized complexity on several types of sparse graphs that are described by structural parameters. In particular, we provide kernelization algorithms and kernel lower bounds for these problems. A somewhat surprising consequence of our kernelizations is that Partial Vertex Cover and Max (k,n-k)-Cut not only behave in the same way but that the kernels for both problems can be obtained by the same algorithms

    Kernelization and Sparseness: the case of Dominating Set

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    We prove that for every positive integer rr and for every graph class G\mathcal G of bounded expansion, the rr-Dominating Set problem admits a linear kernel on graphs from G\mathcal G. Moreover, when G\mathcal G is only assumed to be nowhere dense, then we give an almost linear kernel on G\mathcal G for the classic Dominating Set problem, i.e., for the case r=1r=1. These results generalize a line of previous research on finding linear kernels for Dominating Set and rr-Dominating Set. However, the approach taken in this work, which is based on the theory of sparse graphs, is radically different and conceptually much simpler than the previous approaches. We complement our findings by showing that for the closely related Connected Dominating Set problem, the existence of such kernelization algorithms is unlikely, even though the problem is known to admit a linear kernel on HH-topological-minor-free graphs. Also, we prove that for any somewhere dense class G\mathcal G, there is some rr for which rr-Dominating Set is W[22]-hard on G\mathcal G. Thus, our results fall short of proving a sharp dichotomy for the parameterized complexity of rr-Dominating Set on subgraph-monotone graph classes: we conjecture that the border of tractability lies exactly between nowhere dense and somewhere dense graph classes.Comment: v2: new author, added results for r-Dominating Sets in bounded expansion graph

    The Graph Motif problem parameterized by the structure of the input graph

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    The Graph Motif problem was introduced in 2006 in the context of biological networks. It consists of deciding whether or not a multiset of colors occurs in a connected subgraph of a vertex-colored graph. Graph Motif has been mostly analyzed from the standpoint of parameterized complexity. The main parameters which came into consideration were the size of the multiset and the number of colors. Though, in the many applications of Graph Motif, the input graph originates from real-life and has structure. Motivated by this prosaic observation, we systematically study its complexity relatively to graph structural parameters. For a wide range of parameters, we give new or improved FPT algorithms, or show that the problem remains intractable. For the FPT cases, we also give some kernelization lower bounds as well as some ETH-based lower bounds on the worst case running time. Interestingly, we establish that Graph Motif is W[1]-hard (while in W[P]) for parameter max leaf number, which is, to the best of our knowledge, the first problem to behave this way.Comment: 24 pages, accepted in DAM, conference version in IPEC 201
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