1,173 research outputs found

    Semi-Streaming Set Cover

    Full text link
    This paper studies the set cover problem under the semi-streaming model. The underlying set system is formalized in terms of a hypergraph G=(V,E)G = (V, E) whose edges arrive one-by-one and the goal is to construct an edge cover FEF \subseteq E with the objective of minimizing the cardinality (or cost in the weighted case) of FF. We consider a parameterized relaxation of this problem, where given some 0ϵ<10 \leq \epsilon < 1, the goal is to construct an edge (1ϵ)(1 - \epsilon)-cover, namely, a subset of edges incident to all but an ϵ\epsilon-fraction of the vertices (or their benefit in the weighted case). The key limitation imposed on the algorithm is that its space is limited to (poly)logarithmically many bits per vertex. Our main result is an asymptotically tight trade-off between ϵ\epsilon and the approximation ratio: We design a semi-streaming algorithm that on input graph GG, constructs a succinct data structure D\mathcal{D} such that for every 0ϵ<10 \leq \epsilon < 1, an edge (1ϵ)(1 - \epsilon)-cover that approximates the optimal edge \mbox{(11-)cover} within a factor of f(ϵ,n)f(\epsilon, n) can be extracted from D\mathcal{D} (efficiently and with no additional space requirements), where f(ϵ,n)={O(1/ϵ),if ϵ>1/nO(n),otherwise. f(\epsilon, n) = \left\{ \begin{array}{ll} O (1 / \epsilon), & \text{if } \epsilon > 1 / \sqrt{n} \\ O (\sqrt{n}), & \text{otherwise} \end{array} \right. \, . In particular for the traditional set cover problem we obtain an O(n)O(\sqrt{n})-approximation. This algorithm is proved to be best possible by establishing a family (parameterized by ϵ\epsilon) of matching lower bounds.Comment: Full version of the extended abstract that will appear in Proceedings of ICALP 2014 track

    Approximate Hypergraph Coloring under Low-discrepancy and Related Promises

    Get PDF
    A hypergraph is said to be χ\chi-colorable if its vertices can be colored with χ\chi colors so that no hyperedge is monochromatic. 22-colorability is a fundamental property (called Property B) of hypergraphs and is extensively studied in combinatorics. Algorithmically, however, given a 22-colorable kk-uniform hypergraph, it is NP-hard to find a 22-coloring miscoloring fewer than a fraction 2k+12^{-k+1} of hyperedges (which is achieved by a random 22-coloring), and the best algorithms to color the hypergraph properly require n11/k\approx n^{1-1/k} colors, approaching the trivial bound of nn as kk increases. In this work, we study the complexity of approximate hypergraph coloring, for both the maximization (finding a 22-coloring with fewest miscolored edges) and minimization (finding a proper coloring using fewest number of colors) versions, when the input hypergraph is promised to have the following stronger properties than 22-colorability: (A) Low-discrepancy: If the hypergraph has discrepancy k\ell \ll \sqrt{k}, we give an algorithm to color the it with nO(2/k)\approx n^{O(\ell^2/k)} colors. However, for the maximization version, we prove NP-hardness of finding a 22-coloring miscoloring a smaller than 2O(k)2^{-O(k)} (resp. kO(k)k^{-O(k)}) fraction of the hyperedges when =O(logk)\ell = O(\log k) (resp. =2\ell=2). Assuming the UGC, we improve the latter hardness factor to 2O(k)2^{-O(k)} for almost discrepancy-11 hypergraphs. (B) Rainbow colorability: If the hypergraph has a (k)(k-\ell)-coloring such that each hyperedge is polychromatic with all these colors, we give a 22-coloring algorithm that miscolors at most kΩ(k)k^{-\Omega(k)} of the hyperedges when k\ell \ll \sqrt{k}, and complement this with a matching UG hardness result showing that when =k\ell =\sqrt{k}, it is hard to even beat the 2k+12^{-k+1} bound achieved by a random coloring.Comment: Approx 201

    Sufficient Conditions for Tuza's Conjecture on Packing and Covering Triangles

    Full text link
    Given a simple graph G=(V,E)G=(V,E), a subset of EE is called a triangle cover if it intersects each triangle of GG. Let νt(G)\nu_t(G) and τt(G)\tau_t(G) denote the maximum number of pairwise edge-disjoint triangles in GG and the minimum cardinality of a triangle cover of GG, respectively. Tuza conjectured in 1981 that τt(G)/νt(G)2\tau_t(G)/\nu_t(G)\le2 holds for every graph GG. In this paper, using a hypergraph approach, we design polynomial-time combinatorial algorithms for finding small triangle covers. These algorithms imply new sufficient conditions for Tuza's conjecture on covering and packing triangles. More precisely, suppose that the set TG\mathscr T_G of triangles covers all edges in GG. We show that a triangle cover of GG with cardinality at most 2νt(G)2\nu_t(G) can be found in polynomial time if one of the following conditions is satisfied: (i) νt(G)/TG13\nu_t(G)/|\mathscr T_G|\ge\frac13, (ii) νt(G)/E14\nu_t(G)/|E|\ge\frac14, (iii) E/TG2|E|/|\mathscr T_G|\ge2. Keywords: Triangle cover, Triangle packing, Linear 3-uniform hypergraphs, Combinatorial algorithm

    Incremental complexity of a bi-objective hypergraph transversal problem

    Get PDF
    The hypergraph transversal problem has been intensively studied, from both a theoretical and a practical point of view. In particular , its incremental complexity is known to be quasi-polynomial in general and polynomial for bounded hypergraphs. Recent applications in computational biology however require to solve a generalization of this problem, that we call bi-objective transversal problem. The instance is in this case composed of a pair of hypergraphs (A, B), and the aim is to find minimal sets which hit all the hyperedges of A while intersecting a minimal set of hyperedges of B. In this paper, we formalize this problem, link it to a problem on monotone boolean \land -- \lor formulae of depth 3 and study its incremental complexity
    corecore