129 research outputs found

    Exploring Subexponential Parameterized Complexity of Completion Problems

    Get PDF
    Let F{\cal F} be a family of graphs. In the F{\cal F}-Completion problem, we are given a graph GG and an integer kk as input, and asked whether at most kk edges can be added to GG so that the resulting graph does not contain a graph from F{\cal F} as an induced subgraph. It appeared recently that special cases of F{\cal F}-Completion, the problem of completing into a chordal graph known as Minimum Fill-in, corresponding to the case of F={C4,C5,C6,}{\cal F}=\{C_4,C_5,C_6,\ldots\}, and the problem of completing into a split graph, i.e., the case of F={C4,2K2,C5}{\cal F}=\{C_4, 2K_2, C_5\}, are solvable in parameterized subexponential time 2O(klogk)nO(1)2^{O(\sqrt{k}\log{k})}n^{O(1)}. The exploration of this phenomenon is the main motivation for our research on F{\cal F}-Completion. In this paper we prove that completions into several well studied classes of graphs without long induced cycles also admit parameterized subexponential time algorithms by showing that: - The problem Trivially Perfect Completion is solvable in parameterized subexponential time 2O(klogk)nO(1)2^{O(\sqrt{k}\log{k})}n^{O(1)}, that is F{\cal F}-Completion for F={C4,P4}{\cal F} =\{C_4, P_4\}, a cycle and a path on four vertices. - The problems known in the literature as Pseudosplit Completion, the case where F={2K2,C4}{\cal F} = \{2K_2, C_4\}, and Threshold Completion, where F={2K2,P4,C4}{\cal F} = \{2K_2, P_4, C_4\}, are also solvable in time 2O(klogk)nO(1)2^{O(\sqrt{k}\log{k})} n^{O(1)}. We complement our algorithms for F{\cal F}-Completion with the following lower bounds: - For F={2K2}{\cal F} = \{2K_2\}, F={C4}{\cal F} = \{C_4\}, F={P4}{\cal F} = \{P_4\}, and F={2K2,P4}{\cal F} = \{2K_2, P_4\}, F{\cal F}-Completion cannot be solved in time 2o(k)nO(1)2^{o(k)} n^{O(1)} unless the Exponential Time Hypothesis (ETH) fails. Our upper and lower bounds provide a complete picture of the subexponential parameterized complexity of F{\cal F}-Completion problems for F{2K2,C4,P4}{\cal F}\subseteq\{2K_2, C_4, P_4\}.Comment: 32 pages, 16 figures, A preliminary version of this paper appeared in the proceedings of STACS'1

    Fast Biclustering by Dual Parameterization

    Get PDF
    We study two clustering problems, Starforest Editing, the problem of adding and deleting edges to obtain a disjoint union of stars, and the generalization Bicluster Editing. We show that, in addition to being NP-hard, none of the problems can be solved in subexponential time unless the exponential time hypothesis fails. Misra, Panolan, and Saurabh (MFCS 2013) argue that introducing a bound on the number of connected components in the solution should not make the problem easier: In particular, they argue that the subexponential time algorithm for editing to a fixed number of clusters (p-Cluster Editing) by Fomin et al. (J. Comput. Syst. Sci., 80(7) 2014) is an exception rather than the rule. Here, p is a secondary parameter, bounding the number of components in the solution. However, upon bounding the number of stars or bicliques in the solution, we obtain algorithms which run in time 25pk+O(n+m)2^{5 \sqrt{pk}} + O(n+m) for p-Starforest Editing and 2O(pklog(pk))+O(n+m)2^{O(p \sqrt{k} \log(pk))} + O(n+m) for p-Bicluster Editing. We obtain a similar result for the more general case of t-Partite p-Cluster Editing. This is subexponential in k for fixed number of clusters, since p is then considered a constant. Our results even out the number of multivariate subexponential time algorithms and give reasons to believe that this area warrants further study.Comment: Accepted for presentation at IPEC 201

    Polynomial kernelization for removing induced claws and diamonds

    Full text link
    A graph is called (claw,diamond)-free if it contains neither a claw (a K1,3K_{1,3}) nor a diamond (a K4K_4 with an edge removed) as an induced subgraph. Equivalently, (claw,diamond)-free graphs can be characterized as line graphs of triangle-free graphs, or as linear dominoes, i.e., graphs in which every vertex is in at most two maximal cliques and every edge is in exactly one maximal clique. In this paper we consider the parameterized complexity of the (claw,diamond)-free Edge Deletion problem, where given a graph GG and a parameter kk, the question is whether one can remove at most kk edges from GG to obtain a (claw,diamond)-free graph. Our main result is that this problem admits a polynomial kernel. We complement this finding by proving that, even on instances with maximum degree 66, the problem is NP-complete and cannot be solved in time 2o(k)V(G)O(1)2^{o(k)}\cdot |V(G)|^{O(1)} unless the Exponential Time Hypothesis fai

    A survey of parameterized algorithms and the complexity of edge modification

    Get PDF
    The survey is a comprehensive overview of the developing area of parameterized algorithms for graph modification problems. It describes state of the art in kernelization, subexponential algorithms, and parameterized complexity of graph modification. The main focus is on edge modification problems, where the task is to change some adjacencies in a graph to satisfy some required properties. To facilitate further research, we list many open problems in the area.publishedVersio

    Fast Biclustering by Dual Parameterization

    Get PDF
    We study two clustering problems, Starforest Editing, the problem of adding and deleting edges to obtain a disjoint union of stars, and the generalization Bicluster Editing. We show that, in addition to being NP-hard, none of the problems can be solved in subexponential time unless the exponential time hypothesis fails. Misra, Panolan, and Saurabh (MFCS 2013) argue that introducing a bound on the number of connected components in the solution should not make the problem easier: In particular, they argue that the subexponential time algorithm for editing to a fixed number of clusters (p-Cluster Editing) by Fomin et al. (J. Comput. Syst. Sci., 80(7) 2014) is an exception rather than the rule. Here, p is a secondary parameter, bounding the number of components in the solution. However, upon bounding the number of stars or bicliques in the solution, we obtain algorithms which run in time O(2^{3*sqrt(pk)} + n + m) for p-Starforest Editing and O(2^{O(p * sqrt(k) * log(pk))} + n + m) for p-Bicluster Editing. We obtain a similar result for the more general case of t-Partite p-Cluster Editing. This is subexponential in k for a fixed number of clusters, since p is then considered a constant. Our results even out the number of multivariate subexponential time algorithms and give reasons to believe that this area warrants further study

    Unit Interval Editing is Fixed-Parameter Tractable

    Full text link
    Given a graph~GG and integers k1k_1, k2k_2, and~k3k_3, the unit interval editing problem asks whether GG can be transformed into a unit interval graph by at most k1k_1 vertex deletions, k2k_2 edge deletions, and k3k_3 edge additions. We give an algorithm solving this problem in time 2O(klogk)(n+m)2^{O(k\log k)}\cdot (n+m), where k:=k1+k2+k3k := k_1 + k_2 + k_3, and n,mn, m denote respectively the numbers of vertices and edges of GG. Therefore, it is fixed-parameter tractable parameterized by the total number of allowed operations. Our algorithm implies the fixed-parameter tractability of the unit interval edge deletion problem, for which we also present a more efficient algorithm running in time O(4k(n+m))O(4^k \cdot (n + m)). Another result is an O(6k(n+m))O(6^k \cdot (n + m))-time algorithm for the unit interval vertex deletion problem, significantly improving the algorithm of van 't Hof and Villanger, which runs in time O(6kn6)O(6^k \cdot n^6).Comment: An extended abstract of this paper has appeared in the proceedings of ICALP 2015. Update: The proof of Lemma 4.2 has been completely rewritten; an appendix is provided for a brief overview of related graph classe
    corecore