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Christophe Paul

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9 papers
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9

FOCS Conference 2024 Conference Paper

Obstructions to Erdös-Pósa Dualities for Minors

  • Christophe Paul
  • Evangelos Protopapas
  • Dimitrios M. Thilikos
  • Sebastian Wiederrecht

Let $\mathcal{G}$ and $\mathcal{H}$ be minor-closed graph classes. We say that the pair $(\mathcal{H}, \ \mathcal{G})$ is an Erdös-Pósa pair (EP-pair) if there exists a function $f$ such that for every $k$ and every graph $G\in \mathcal{G}$, either $G$ has $k$ pairwise vertex-disjoint sub graphs which do not belong to $\mathcal{H}$, or there exists a set $S\subseteq V(G)$ of size at most $f(k)$ for which $G-S\in \mathcal{H}$. The classic result of Erdös and Pósa says that if $\mathcal{F}$ is the class of forests, then $(\mathcal{F}, \mathcal{G})$ is an EP-pair for all graph classes $\mathcal{G}$. A minor-closed graph class $\mathcal{G}$ is an EP-counterexample for $\mathcal{H}$ if $\mathcal{G}$ is minimal with the property that $(\mathcal{H}, \ \mathcal{G})$ is not an EP-pair. In this paper, we prove that for every minor-closed graph class $\mathcal{H}$ the set $\mathfrak{C}_{\mathcal{H}}$ of all EP-counterexamples for $\mathcal{H}$ is finite. In particular, we provide a complete characterization of $\mathfrak{C}_{\mathcal{H}}$ for every $\mathcal{H}$ and give a constructive upper bound on its size. We show that each class $\mathcal{G}$ in $\mathfrak{C}_{\mathcal{H}}$ can be described as the set of all minors of some, suitably defined, sequence of grid-like graphs $\langle{W}_{k}\rangle_{k\in \mathbb{N}}$. Moreover, each $\mathrm{W}_{k}$ admits a half-integral packing, i. e. , $k$ copies of some $H\not\in \mathcal{H}$ where no vertex is used more than twice. This implies a complete delineation of the half-integrality threshold of the Erdös-Pósa property for minors and as a corollary, we obtain a constructive proof of Thomas' conjecture on the half-integral Erdös-Pósa property for minors which was recently confirmed by Liu. Our results are algorithmic. Let $h=h(\mathcal{H})$ denote the maximum size of an obstruction to $\mathcal{H}$. For every minor-closed graph class $\mathcal{H}$, we construct an algorithm that, given a graph $G$ and an integer $k$, either outputs a half-integral packing of $k$ copies of some $H\not\in \mathcal{H}$ or outputs a set of at most $2^{k^{\overline{\mathcal{O}}_{h}(1)}}$ vertices whose deletion creates a graph in $\mathcal{H}$ in time $2^{2^{k^{\mathcal{O}_{h}(1)}}}\cdot\vert G\vert ^{4}\log\vert G\vert$. Moreover, as a consequence of our results, for every minor-closed class $\mathcal{H}$, we obtain min-max-dualities, which may be seen as analogues of the celebrated Grid Theorem of Robertson and Seymour, for the recently introduced parameters $\mathcal{H}$ -treewidth and elimination distance to $\mathcal{H}$.

TCS Journal 2020 Journal Article

Edge degeneracy: Algorithmic and structural results

  • Stratis Limnios
  • Christophe Paul
  • Joanny Perret
  • Dimitrios M. Thilikos

We consider a cops and robber game where the cops are blocking edges of a graph, while the robber occupies its vertices. At each round of the game, the cops choose some set of edges to block and right after the robber is obliged to move to another vertex traversing at most s unblocked edges (s can be seen as the speed of the robber). Both parts have complete knowledge of the opponent's moves and the cops win when they occupy all edges incident to the robbers position. We introduce the capture cost on G against a robber of speed s. This defines a hierarchy of invariants, namely δ e 1, δ e 2, …, δ e ∞, where δ e ∞ is an edge-analogue of the admissibility graph invariant, namely the edge-admissibility of a graph. We prove that the problem asking whether δ e s ( G ) ≤ k, is polynomially solvable when s ∈ { 1, 2, 3, ∞ } while, otherwise, it is NP-complete. Our main result is a structural theorem for graphs of bounded edge-admissibility. We prove that every graph of edge-admissibility at most k can be constructed using ( ≤ k ) -edge-sums, starting from graphs whose all vertices, except possibly from one, have degree at most k. Our structural result is approximately tight in the sense that graphs generated by this construction always have edge-admissibility at most 2 k − 1. Our proofs are based on a precise structural characterization of the graphs that do not contain θ r as an immersion, where θ r is the graph on two vertices and r parallel edges.

MFCS Conference 2020 Conference Paper

Hierarchical Clusterings of Unweighted Graphs

  • Svein Høgemo
  • Christophe Paul
  • Jan Arne Telle

We study the complexity of finding an optimal hierarchical clustering of an unweighted similarity graph under the recently introduced Dasgupta objective function. We introduce a proof technique, called the normalization procedure, that takes any such clustering of a graph G and iteratively improves it until a desired target clustering of G is reached. We use this technique to show both a negative and a positive complexity result. Firstly, we show that in general the problem is NP-complete. Secondly, we consider min-well-behaved graphs, which are graphs H having the property that for any k the graph H^{(k)} being the join of k copies of H has an optimal hierarchical clustering that splits each copy of H in the same optimal way. To optimally cluster such a graph H^{(k)} we thus only need to optimally cluster the smaller graph H. Co-bipartite graphs are min-well-behaved, but otherwise they seem to be scarce. We use the normalization procedure to show that also the cycle on 6 vertices is min-well-behaved.

TCS Journal 2017 Journal Article

Parameterized complexity of the MINCCA problem on graphs of bounded decomposability

  • Didem Gözüpek
  • Sibel Özkan
  • Christophe Paul
  • Ignasi Sau
  • Mordechai Shalom

In an edge-colored graph, the cost incurred at a vertex on a path when two incident edges with different colors are traversed is called reload or changeover cost. The Minimum Changeover Cost Arborescence (MinCCA) problem consists in finding an arborescence with a given root vertex such that the total changeover cost of the internal vertices is minimized. It has been recently proved by Gözüpek et al. (2016) that the MinCCA problem when parameterized by the treewidth and the maximum degree of the input graph is in FPT. In this article we present the following hardness results for MinCCA: • the problem is W[1]-hard when parameterized by the vertex cover number of the input graph, even on graphs of degeneracy at most 3. In particular, it is W[1]-hard parameterized by the treewidth of the input graph, which answers the main open problem in the work of Gözüpek et al. (2016); • it is W[1]-hard on multigraphs parameterized by the tree-cutwidth of the input multigraph; and • it remains NP -hard on planar graphs even when restricted to instances with at most 6 colors and 0/1 symmetric costs, or when restricted to instances with at most 8 colors, maximum degree bounded by 4, and 0/1 symmetric costs.

MFCS Conference 2011 Conference Paper

Conflict Packing Yields Linear Vertex-Kernels for k -FAST, k -dense RTI and a Related Problem

  • Christophe Paul
  • Anthony Perez 0001
  • Stéphan Thomassé

Abstract We develop a technique that we call Conflict Packing in the context of kernelization [7]. We illustrate this technique on several well-studied problems: Feedback Arc Set in Tournaments, Dense Rooted Triplet Inconsistency and Betweenness in Tournaments. For the former, one is given a tournament T = ( V, A ) and seeks a set of at most k arcs whose reversal in T results in an acyclic tournament. While a linear vertex-kernel is already known for this problem [6], using the Conflict Packing allows us to find a so-called safe partition, the central tool of the kernelization algorithm in [6], with simpler arguments. Regarding the Dense Rooted Triplet Inconsistency problem, one is given a set of vertices V and a dense collection \(\mathcal{R}\) of rooted binary trees over three vertices of V and seeks a rooted tree over V containing all but at most k triplets from \(\mathcal{R}\). Using again the Conflict Packing, we prove that the Dense Rooted Triplet Inconsistency problem admits a linear vertex-kernel. This result improves the best known bound of O ( k 2) vertices for this problem [16]. Finally, we use this technique to obtain a linear vertex-kernel for Betweenness in Tournaments, where one is given a set of vertices V and a dense collection \(\mathcal{R}\) of betweenness triplets and seeks an ordering containing all but at most k triplets from \(\mathcal{R}\). To the best of our knowledge this result constitutes the first polynomial kernel for the problem.

TCS Journal 2008 Journal Article

Competitive graph searches

  • Binh-Minh Bui-Xuan
  • Michel Habib
  • Christophe Paul

We exemplify an optimization criterion for divide-and-conquer algorithms with a technique called generic competitive graph search. The technique is then applied to solve two problems arising from biocomputing, so-called Common Connected Components and Cograph Sandwich. The first problem can be defined as follows: given two graphs on the same set of n vertices, find the coarsest partition of the vertex set into subsets which induce connected subgraphs in both input graphs. The second problem is an instance of sandwich problems: given a partial subgraph G 1 of G 2, find a partial subgraph G of G 2 that is partial supergraph of G 1 (sandwich), and that is a cograph. For the former problem our generic algorithm not only achieves the current best known performance on arbitrary graphs and forests, but also improves by a log n factor when the input is made of planar graphs. However, our complexity for intervals graphs is slightly lower than a recent result. For the latter problem, we first study the relationship between the common connected components problem and the cograph sandwich problem, then, using our competitive graph search paradigm, we improve the computation of cograph sandwiches from O ( n ( n + m ) ) down to O ( n + m log 2 n ), where n is the number of vertices and m of total edges.

STOC Conference 2007 Conference Paper

Interval completion with few edges

  • Pinar Heggernes
  • Christophe Paul
  • Jan Arne Telle
  • Yngve Villanger

We present an algorithm with runtime O(k (2k) n 3 * m) for the following NP-complete problem: Given an arbitrary graph G on n vertices and m edges, can we obtain an interval graph by adding at most k new edges to G? This resolves the long-standing open question, first posed by Kaplan, Shamir and Tarjan, of whether this problem could be solved in time f(k) * n (O(1)) .The problem has applications in Physical Mapping of DNA and in Profile Minimization for Sparse Matrix Computations. For the first application, our results show tractability for the case of a small number k of false negative errors, and for the second, a small number k of zero elements in the envelope.

TCS Journal 2001 Journal Article

A simple paradigm for graph recognition: application to cographs and distance hereditary graphs

  • Guillaume Damiand
  • Michel Habib
  • Christophe Paul

An easy way for graph recognition algorithms is to use a two-step process: first, compute a characteristic feature as if the graph belongs to that class; second, check whether the computed feature really defines the input graph. Although in some cases the two steps can be merged, separating them may yield new and much more easily understood algorithms. In this paper we apply that paradigm to the cograph and distance hereditary graph recognition problems.

TCS Journal 2000 Journal Article

Lex-BFS and partition refinement, with applications to transitive orientation, interval graph recognition and consecutive ones testing

  • Michel Habib
  • Ross McConnell
  • Christophe Paul
  • Laurent Viennot

By making use of lexicographic breadth first search (Lex-BFS) and partition refinement with pivots, we obtain very simple algorithms for some well-known problems in graph theory. We give a O(n+mlogn) algorithm for transitive orientation of a comparability graph, and simple linear algorithms to recognize interval graphs, convex graphs, Y-semichordal graphs and matrices that have the consecutive ones property. Previous approaches to these problems used difficult preprocessing steps, such as computing PQ-trees or modular decomposition. The algorithms we give are easy to understand and straightforward to prove. They do not make use of sophisticated data structures, and the complexity analysis is straightforward.

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