arXiv subjects

Guillaume Ducoffe

Publications and source records attributed to Guillaume Ducoffe.

35 records · Page 2Linked to original sources

arXiv2020

Optimal diameter computation within bounded clique-width graphs

Coudert et al. (SODA'18) proved that under the Strong Exponential-Time Hypothesis, for any $ε>0$, there is no ${\cal O}(2^{o(k)}n^{2-ε})$-time algorithm for computing the diameter within the $n$-vertex cubic graphs of clique-width at most $k$. We present an algorithm which given an $n$-vertex $m$-edge graph $G$ and a $k$-expression, computes all the eccentricities in ${\cal O}(2^{{\cal O}(k)}(n+m)^{1+o(1)})$ time, thus matching their conditional lower bound. It can be modified in order to compute the Wiener index and the median set of $G$ within the same amount of time. On our way, we get a distance-labeling scheme for $n$-vertex $m$-edge graphs of clique-width at most $k$, using ${\cal O}(k\log^2{n})$ bits per vertex and constructible in ${\cal O}(k(n+m)\log{n})$ time from a given $k$-expression. Doing so, we match the label size obtained by Courcelle and Vanicat (DAM 2016), while we considerably improve the dependency on $k$ in their scheme. As a corollary, we get an ${\cal O}(kn^2\log{n})$-time algorithm for computing All-Pairs Shortest-Paths on $n$-vertex graphs of clique-width at most $k$. This partially answers an open question of Kratsch and Nelles (STACS'20).

cs.DS↗

arXiv2020

Distance problems within Helly graphs and $k$-Helly graphs

The ball hypergraph of a graph $G$ is the family of balls of all possible centers and radii in $G$. It has Helly number at most $k$ if every subfamily of $k$-wise intersecting balls has a nonempty common intersection. A graph is $k$-Helly (or Helly, if $k=2$) if its ball hypergraph has Helly number at most $k$. We prove that a central vertex and all the medians in an $n$-vertex $m$-edge Helly graph can be computed w.h.p. in $\tilde{\cal O}(m\sqrt{n})$ time. Both results extend to a broader setting where we define a non-negative cost function over the vertex-set. For any fixed $k$, we also present an $\tilde{\cal O}(m\sqrt{kn})$-time randomized algorithm for radius computation within $k$-Helly graphs. If we relax the definition of Helly number (for what is sometimes called an "almost Helly-type" property in the literature), then our approach leads to an approximation algorithm for computing the radius with an additive one-sided error of at most some constant.

cs.DS↗

arXiv2020

Eccentricity queries and beyond using Hub Labels

Hub labeling schemes are popular methods for computing distances on road networks and other large complex networks, often answering to a query within a few microseconds for graphs with millions of edges. In this work, we study their algorithmic applications beyond distance queries. We focus on eccentricity queries and distance-sum queries, for several versions of these problems on directed weighted graphs, that is in part motivated by their importance in facility location problems. On the negative side, we show conditional lower bounds for these above problems on unweighted undirected sparse graphs, via standard constructions from "Fine-grained" complexity. However, things take a different turn when the hub labels have a sublogarithmic size. Indeed, given a hub labeling of maximum label size $\leq k$, after pre-processing the labels in total $2^{{O}(k)} \cdot |V|^{1+o(1)}$ time, we can compute both the eccentricity and the distance-sum of any vertex in $2^{{O}(k)} \cdot |V|^{o(1)}$ time. It can also be applied to the fast global computation of some topological indices. Finally, as a by-product of our approach, on any fixed class of unweighted graphs with bounded expansion, we can decide whether the diameter of an $n$-vertex graph in the class is at most $k$ in $f(k) \cdot n^{1+o(1)}$ time, for some "explicit" function $f$.

cs.DS↗

arXiv2020

Isometric embeddings in trees and their use in the diameter problem

We prove that given a discrete space with $n$ points which is either embedded in a system of $k$ trees, or the Cartesian product of $k$ trees, we can compute all eccentricities in ${\cal O}(2^{{\cal O}(k\log{k})}(N+n)^{1+o(1)})$ time, where $N$ is the cumulative total order over all these $k$ trees. This is near optimal under the Strong Exponential-Time Hypothesis, even in the very special case of an $n$-vertex graph embedded in a system of $ω(\log{n})$ spanning trees. However, given such an embedding in the strong product of $k$ trees, there is a much faster ${\cal O}(N + kn)$-time algorithm for this problem. All our positive results can be turned into approximation algorithms for the graphs and finite spaces with a quasi isometric embedding in trees, if such embedding is given as input, where the approximation factor (resp., the approximation constant) depends on the distortion of the embedding (resp., of its stretch). The existence of embeddings in the Cartesian product of finitely many trees has been thoroughly investigated for cube-free median graphs. We give the first-known quasi linear-time algorithm for computing the diameter within this graph class. It does not require an embedding in a product of trees to be given as part of the input. On our way, being given an $n$-node tree $T$, we propose a data structure with ${\cal O}(n\log{n})$ pre-processing time in order to compute in ${\cal O}(k\log^2{n})$ time the eccentricity of any subset of $k$ nodes. We combine the latter technical contribution, of independent interest, with a recent distance-labeling scheme that was designed for cube-free median graphs.

cs.DS↗

arXiv2020

Around the diameter of AT-free graphs

A graph algorithm is truly subquadratic if it runs in ${\cal O}(m^b)$ time on connected $m$-edge graphs, for some positive $b < 2$. Roditty and Vassilevska Williams (STOC'13) proved that under plausible complexity assumptions, there is no truly subquadratic algorithm for computing the diameter of general graphs. In this work, we present positive and negative results on the existence of such algorithms for computing the diameter on some special graph classes. Specifically, three vertices in a graph form an asteroidal triple (AT) if between any two of them there exists a path that avoids the closed neighbourhood of the third one. We call a graph AT-free if it does not contain an AT. We first prove that for all $m$-edge AT-free graphs, one can compute all the eccentricities in truly subquadratic ${\cal O}(m^{3/2})$ time. Then, we extend our study to several subclasses of chordal graphs -- all of them generalizing interval graphs in various ways --, as an attempt to understand which of the properties of AT-free graphs, or natural generalizations of the latter, can help in the design of fast algorithms for the diameter problem on broader graph classes. For instance, for all chordal graphs with a dominating shortest path, there is a linear-time algorithm for computing a diametral pair if the diameter is at least four. However, already for split graphs with a dominating edge, under plausible complexity assumptions, there is no truly subquadratic algorithm for deciding whether the diameter is either $2$ or $3$.

cs.DS↗

arXiv2019

A story of diameter, radius and Helly property

A graph is Helly if every family of pairwise intersecting balls has a nonempty common intersection. Motivated by previous work on dually chordal graphs and graphs of bounded distance VC-dimension we prove several new results on the complexity of computing the diameter and the radius on Helly graphs and related graph classes. * First, we present algorithms which given an $n$-vertex $m$-edge Helly graph $G$ as input, compute w.h.p. its radius and its diameter in time $\tilde{\cal O}(m\sqrt{n})$. Our algorithms are based on the Helly property and on several implications of the unimodality of the eccentricity function in Helly graphs: every vertex of locally minimum eccentricity is a central vertex. * Then, we focus on $C_4$-free Helly graphs, which include, amongst other subclasses, bridged Helly graphs and so, chordal Helly graphs and hereditary Helly graphs. For the $C_4$-free Helly graphs, we present linear-time algorithms for computing the eccentricity of all vertices. Doing so, we generalize previous results on strongly chordal graphs to a much larger subclass. * Finally, we derive from our findings on chordal Helly graphs a more general one-to-many reduction from diameter computation on chordal graphs to either diameter computation on split graphs or the {\sc Disjoint Set} problem. Therefore, split graphs are in some sense the {\em only} hard instances for diameter computation on chordal graphs. As a byproduct of our reduction the eccentricity of all vertices in a chordal graph can be approximated in ${\cal O}(m\log{n})$ time with an additive one-sided error of at most one, and on any subclass of chordal graphs with constant VC-dimension the diameter can be computed in truly subquadratic time. These above results are a new step toward better understanding the role of abstract geometric properties in the fast computation of metric graph invariants.

cs.DS↗

arXiv2019

Diameter computation on $H$-minor free graphs and graphs of bounded (distance) VC-dimension

We propose to study unweighted graphs of constant distance VC-dimension as a broad generalization of many graph classes for which we can compute the diameter in truly subquadratic-time. In particular for any fixed $H$, the class of $H$-minor free graphs has distance VC-dimension at most $|V(H)|-1$. Our first main result is that on graphs of distance VC-dimension at most $d$, for any fixed $k$ we can either compute the diameter or conclude that it is larger than $k$ in time $\tilde{\cal O}(k\cdot mn^{1-\varepsilon_d})$, where $\varepsilon_d \in (0;1)$ only depends on $d$. Then as a byproduct of our approach, we get the first truly subquadratic-time algorithm for constant diameter computation on all the nowhere dense graph classes. Finally, we show how to remove the dependency on $k$ for any graph class that excludes a fixed graph $H$ as a minor. More generally, our techniques apply to any graph with constant distance VC-dimension and polynomial expansion. As a result for all such graphs one obtains a truly subquadratic-time algorithm for computing their diameter. Our approach is based on the work of Chazelle and Welzl who proved the existence of spanning paths with strongly sublinear stabbing number for every hypergraph of constant VC-dimension. We show how to compute such paths efficiently by combining the best known approximation algorithms for the stabbing number problem with a clever use of $\varepsilon$-nets, region decomposition and other partition techniques.

cs.DS↗

arXiv2019

Fast approximation and exact computation of negative curvature parameters of graphs

In this paper, we study Gromov hyperbolicity and related parameters, that represent how close (locally) a metric space is to a tree from a metric point of view. The study of Gromov hyperbolicity for geodesic metric spaces can be reduced to the study of graph hyperbolicity. The main contribution of this paper is a new characterization of the hyperbolicity of graphs. This characterization has algorithmic implications in the field of large-scale network analysis. A sharp estimate of graph hyperbolicity is useful, e.g., in embedding an undirected graph into hyperbolic space with minimum distortion [Verbeek and Suri, SoCG'14]. The hyperbolicity of a graph can be computed in polynomial-time, however it is unlikely that it can be done in subcubic time. This makes this parameter difficult to compute or to approximate on large graphs. Using our new characterization of graph hyperbolicity, we provide a simple factor 8 approximation algorithm for computing the hyperbolicity of an $n$-vertex graph $G=(V,E)$ in optimal time $O(n^2)$ (assuming that the input is the distance matrix of the graph). This algorithm leads to constant factor approximations of other graph-parameters related to hyperbolicity (thinness, slimness, and insize). We also present the first efficient algorithms for exact computation of these parameters. All of our algorithms can be used to approximate the hyperbolicity of a geodesic metric space. We also show that a similar characterization of hyperbolicity holds for all geodesic metric spaces endowed with a geodesic spanning tree. Along the way, we prove that any complete geodesic metric space $(X,d)$ has such a geodesic spanning tree. We hope that this fundamental result can be useful in other contexts.

cs.DS↗

arXiv2019

Polynomial-time Recognition of 4-Steiner Powers

The $k^{th}$-power of a given graph $G=(V,E)$ is obtained from $G$ by adding an edge between every two distinct vertices at a distance at most $k$ in $G$. We call $G$ a $k$-Steiner power if it is an induced subgraph of the $k^{th}$-power of some tree. Our main contribution is a polynomial-time recognition algorithm of $4$-Steiner powers, thereby extending the decade-year-old results of (Lin, Kearney and Jiang, ISAAC'00) for $k=1,2$ and (Chang and Ko, WG'07) for $k=3$. A graph $G$ is termed $k$-leaf power if there is some tree $T$ such that: all vertices in $V(G)$ are leaf-nodes of $T$, and $G$ is an induced subgraph of the $k^{th}$-power of $T$. As a byproduct of our main result, we give the first known polynomial-time recognition algorithm for $6$-leaf powers.

cs.CC↗

arXiv2018

Faster approximation algorithms for computing shortest cycles on weighted graphs

Given an $n$-vertex $m$-edge graph $G$ with non negative edge-weights, the girth of $G$ is the weight of a shortest cycle in $G$. For any graph $G$ with polynomially bounded integer weights, we present a deterministic algorithm that computes, in $\tilde{\cal O}(n^{5/3}+m)$-time, a cycle of weight at most twice the girth of $G$. Our approach combines some new insights on the previous approximation algorithms for this problem (Lingas and Lundell, IPL'09; Roditty and Tov, TALG'13) with Hitting Set based methods that are used for approximate distance oracles and date back from (Thorup and Zwick, JACM'05). Then, we turn our algorithm into a deterministic $(2+\varepsilon)$-approximation for graphs with arbitrary non negative edge-weights, at the price of a slightly worse running-time in $\tilde{\cal O}(n^{5/3}\log^{{\cal O}(1)}{(1/\varepsilon)}+m)$. Finally, if we insist in removing the dependency in the number $m$ of edges, we can transform our algorithms into an $\tilde{\cal O}(n^{5/3})$-time randomized $4$-approximation for the graphs with non negative edge-weights -- assuming the adjacency lists are sorted. Combined with the aforementioned Hitting Set based methods, this algorithm can be derandomized, thereby yielding an $\tilde{\cal O}(n^{5/3})$-time deterministic $4$-approximation for the graphs with polynomially bounded integer weights, and an $\tilde{\cal O}(n^{5/3}\log^{{\cal O}(1)}{(1/\varepsilon)})$-time deterministic $(4+\varepsilon)$-approximation for the graphs with non negative edge-weights. To the best of our knowledge, these are the first known subquadratic-time approximation algorithms for computing the girth of weighted graphs.

cs.DS↗

arXiv2018

Equivalence between pathbreadth and strong pathbreadth

We say that a given graph $G = (V, E)$ has \emph{pathbreadth} at most $ρ$, denoted $\pb(G) \leq ρ$, if there exists a Roberston and Seymour's path decomposition where every bag is contained in the $ρ$-neighbourhood of some vertex. Similarly, we say that $G$ has \emph{strong pathbreadth} at most $ρ$, denoted $\spb(G) \leq ρ$, if there exists a Roberston and Seymour's path decomposition where every bag is the complete $ρ$-neighbourhood of some vertex. It is straightforward that $\pb(G) \leq \spb(G)$ for any graph $G$. Inspired from a close conjecture in [Leitert and Dragan, COCOA'16], we prove in this note that $\spb(G) \leq 4 \cdot \pb(G)$.

cs.CC↗

arXiv2018

A quasi linear-time b-Matching algorithm on distance-hereditary graphs and bounded split-width graphs

We present a quasi linear-time algorithm for Maximum Matching on distance-hereditary graphs and some of their generalizations. This improves on [Dragan, WG'97], who proposed such an algorithm for the subclass of (tent,hexahedron)-free distance-hereditary graphs. Furthermore, our result is derived from a more general one that is obtained for b-Matching. In the (unit cost) b-Matching problem, we are given a graph G = (V, E) together with a nonnegative integer capacity b v for every vertex v $\in$ V. The objective is to assign nonnegative integer weights (x e) e$\in$E so that: for every v $\in$ V the sum of the weights of its incident edges does not exceed b v , and e$\in$E x e is maximized. We present the first algorithm for solving b-Matching on cographs, distance-hereditary graphs and some of their generalizations in quasi linear time. For that, we use a decomposition algorithm that outputs for any graph G a collection of subgraphs of G with no edge-cutsets inducing a complete bipartite subgraph (a.k.a., splits). The latter collection is sometimes called a split decomposition of G. Furthermore, there exists a generic method in order to design graph algorithms based on split decomposition [Rao, DAM'08]. However, this technique only applies to "localized" problems: for which a "best" partial solution for any given subgraph in a split decomposition can be computed almost independently from the remaining of the graph. Such framework does not apply to matching problems since an augmenting path may cross the subgraphs arbitrarily. We introduce a new technique that somehow captures all the partial solutions for a given union of subgraphs in a split decomposition, in a compact and amenable way for algorithms - assuming some piecewise linear assumption holds on the value of such solutions. The latter assumption is shown to hold for b-Matching. Doing so, we prove that solving b-Matching on any pair G, b can be reduced in quasi linear-time to solving this problem on a collection of smaller graphs: that are obtained from the subgraphs in any split decomposition of G by replacing every vertex with a constant-size module. In particular, if G has a split decomposition where all subgraphs have order at most a fixed k, then we can solve b-Matching for G, b in O((k log 2 k)$\times$(m+n)$\times$log ||b|| 1)-time. This answers an open question of [Coudert et al., SODA'18].

cs.DS↗

arXiv2018

The use of a pruned modular decomposition for Maximum Matching algorithms on some graph classes

We address the following general question: given a graph class C on which we can solve Maximum Matching in (quasi) linear time, does the same hold true for the class of graphs that can be modularly decomposed into C ? A major difficulty in this task is that the Maximum Matching problem is not preserved by quotient, thereby making difficult to exploit the structural properties of the quotient subgraphs of the modular decomposition. So far, we are only aware of a recent framework in [Coudert et al., SODA'18] that only applies when the quotient subgraphs have bounded order and/or under additional assumptions on the nontriv-ial modules in the graph. As a first attempt toward improving this framework we study the combined effect of modular decomposition with a pruning process over the quotient subgraphs. More precisely, we remove sequentially from all such subgraphs their so-called one-vertex extensions (i.e., pendant, anti-pendant, twin, universal and isolated vertices). Doing so, we obtain a "pruned modular decomposition", that can be computed in O(m log n)-time. Our main result is that if all the pruned quotient subgraphs have bounded order then a maximum matching can be computed in linear time. This result is mostly based on two pruning rules on pendant and anti-pendant modules -- that are adjacent, respectively, to one or all but one other modules in the graph. Furthermore, these two latter rules are surprisingly intricate and we consider them as our main technical contribution in the paper. We stress that the class of graphs that can be totally decomposed by the pruned modular decomposition contains all the distance-hereditary graphs, and so, it is larger than cographs. In particular, as a byproduct of our approach we also obtain the first known linear-time algorithms for Maximum Matching on distance-hereditary graphs and graphs with modular-treewidth at most one. Finally, we can use an extended version of our framework in order to compute a maximum matching, in linear-time, for all graph classes that can be modularly decomposed into cycles. Our work is the first to explain why the existence of some nice ordering over the modules of a graph, instead of just over its vertices, can help to speed up the computation of maximum matchings on some graph classes.

cs.DS↗

arXiv2017

Fully polynomial FPT algorithms for some classes of bounded clique-width graphs

Parameterized complexity theory has enabled a refined classification of the difficulty of NP-hard optimization problems on graphs with respect to key structural properties, and so to a better understanding of their true difficulties. More recently, hardness results for problems in P were achieved using reasonable complexity theoretic assumptions such as: Strong Exponential Time Hypothesis (SETH), 3SUM and All-Pairs Shortest-Paths (APSP). According to these assumptions, many graph theoretic problems do not admit truly subquadratic algorithms, nor even truly subcubic algorithms (Williams and Williams, FOCS 2010 and Abboud, Grandoni, Williams, SODA 2015). A central technique used to tackle the difficulty of the above mentioned problems is fixed-parameter algorithms for polynomial-time problems with polynomial dependency in the fixed parameter (P-FPT). This technique was introduced by Abboud, Williams and Wang in SODA 2016 and continued by Husfeldt (IPEC 2016) and Fomin et al. (SODA 2017), using the treewidth as a parameter. Applying this technique to clique-width, another important graph parameter, remained to be done. In this paper we study several graph theoretic problems for which hardness results exist such as cycle problems (triangle detection, triangle counting, girth, diameter), distance problems (diameter, eccentricities, Gromov hyperbolicity, betweenness centrality) and maximum matching. We provide hardness results and fully polynomial FPT algorithms, using clique-width and some of its upper-bounds as parameters (split-width, modular-width and $P\_4$-sparseness). We believe that our most important result is an ${\cal O}(k^4 \cdot n + m)$-time algorithm for computing a maximum matching where $k$ is either the modular-width or the $P\_4$-sparseness. The latter generalizes many algorithms that have been introduced so far for specific subclasses such as cographs, $P\_4$-lite graphs, $P\_4$-extendible graphs and $P\_4$-tidy graphs. Our algorithms are based on preprocessing methods using modular decomposition, split decomposition and primeval decomposition. Thus they can also be generalized to some graph classes with unbounded clique-width.

cs.DS↗

arXiv2016

On computing tree and path decompositions with metric constraints on the bags

We here investigate on the complexity of computing the \emph{tree-length} and the \emph{tree-breadth} of any graph $G$, that are respectively the best possible upper-bounds on the diameter and the radius of the bags in a tree decomposition of $G$. \emph{Path-length} and \emph{path-breadth} are similarly defined and studied for path decompositions. So far, it was already known that tree-length is NP-hard to compute. We here prove it is also the case for tree-breadth, path-length and path-breadth. Furthermore, we provide a more detailed analysis on the complexity of computing the tree-breadth. In particular, we show that graphs with tree-breadth one are in some sense the hardest instances for the problem of computing the tree-breadth. We give new properties of graphs with tree-breadth one. Then we use these properties in order to recognize in polynomial-time all graphs with tree-breadth one that are planar or bipartite graphs. On the way, we relate tree-breadth with the notion of \emph{$k$-good} tree decompositions (for $k=1$), that have been introduced in former work for routing. As a byproduct of the above relation, we prove that deciding on the existence of a $k$-good tree decomposition is NP-complete (even if $k=1$). All this answers open questions from the literature.

cs.CC↗

arXiv2014

XRay: Enhancing the Web's Transparency with Differential Correlation

Today's Web services - such as Google, Amazon, and Facebook - leverage user data for varied purposes, including personalizing recommendations, targeting advertisements, and adjusting prices. At present, users have little insight into how their data is being used. Hence, they cannot make informed choices about the services they choose. To increase transparency, we developed XRay, the first fine-grained, robust, and scalable personal data tracking system for the Web. XRay predicts which data in an arbitrary Web account (such as emails, searches, or viewed products) is being used to target which outputs (such as ads, recommended products, or prices). XRay's core functions are service agnostic and easy to instantiate for new services, and they can track data within and across services. To make predictions independent of the audited service, XRay relies on the following insight: by comparing outputs from different accounts with similar, but not identical, subsets of data, one can pinpoint targeting through correlation. We show both theoretically, and through experiments on Gmail, Amazon, and YouTube, that XRay achieves high precision and recall by correlating data from a surprisingly small number of extra accounts.

cs.NI↗

arXiv2014

Can Selfish Groups be Self-Enforcing?

Algorithmic graph theory has thoroughly analyzed how, given a network describing constraints between various nodes, groups can be formed among these so that the resulting configuration optimizes a \emph{global} metric. In contrast, for various social and economic networks, groups are formed \emph{de facto} by the choices of selfish players. A fundamental problem in this setting is the existence and convergence to a \emph{self-enforcing} configuration: assignment of players into groups such that no player has an incentive to move into another group than hers. Motivated by information sharing on social networks -- and the difficult tradeoff between its benefits and the associated privacy risk -- we study the possible emergence of such stable configurations in a general selfish group formation game. Our paper considers this general game for the first time, and it completes its analysis. We show that convergence critically depends on the level of \emph{collusions} among the players -- which allow multiple players to move simultaneously as long as \emph{all of them} benefit. Solving a previously open problem we exactly show when, depending on collusions, convergence occurs within polynomial time, non-polynomial time, and when it never occurs. We also prove that previously known bounds on convergence time are all loose: by a novel combinatorial analysis of the evolution of this game we are able to provide the first \emph{asymptotically exact} formula on its convergence. Moreover, we extend these results by providing a complete analysis when groups may \emph{overlap}, and for general utility functions representing \emph{multi-modal} interactions. Finally, we prove that collusions have a significant and \emph{positive} effect on the \emph{efficiency} of the equilibrium that is attained.

cs.DM↗