Robust and Approximative Algorithms on Particular Graph Classes Dagstuhl Seminar
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
A Complexity Theory for Implicit Graph Representations
A Complexity Theory for Implicit Graph Representations Maurice Chandoo Leibniz Universität Hannover, Theoretical Computer Science, Appelstr. 4, 30167 Hannover, Germany [email protected] Abstract In an implicit graph representation the vertices of a graph are assigned short labels such that adjacency of two vertices can be algorithmically determined from their labels. This allows for a space-efficient representation of graph classes that have asymptotically fewer graphs than the class of all graphs such as forests or planar graphs. A fundamental question is whether every smaller graph class has such a representation. We consider how restricting the computational complexity of such representations affects what graph classes can be represented. A formal language can be seen as implicit graph representation and therefore complexity classes such as P or NP can be understood as set of graph classes. We investigate this complexity landscape and introduce complexity classes defined in terms of first order logic that capture surprisingly many of the graph classes for which an implicit representation is known. Additionally, we provide a notion of reduction between graph classes which reveals that trees and interval graphs are ‘complete’ for certain fragments of first order logic in this setting. 1998 ACM Subject Classification G.2.2 Graph Theory, F.1.3 Complexity Measures and Classes Keywords and phrases adjacency labeling schemes, complexity of graph properties We call a graph class small if it has at most 2O(n log n) graphs on n vertices. Many important graph classes such as interval graphs are small. Using adjacency matrices or lists to represent such classes is not space-efficient since this requires n2 bits (resp. -
Abstracting Abstraction in Search II: Complexity Analysis
Proceedings of the Fifth Annual Symposium on Combinatorial Search Abstracting Abstraction in Search II: Complexity Analysis Christer Backstr¨ om¨ and Peter Jonsson Department of Computer Science, Linkoping¨ University SE-581 83 Linkoping,¨ Sweden [email protected] [email protected] Abstract In our earlier publication (Backstr¨ om¨ and Jonsson 2012) we have demonstrated the usefulness of this framework in Modelling abstraction as a function from the original state various ways. We have shown that a certain combination of space to an abstract state space is a common approach in com- our transformation properties exactly captures the DPP con- binatorial search. Sometimes this is too restricted, though, cept by Zilles and Holte (2010). A related concept is that and we have previously proposed a framework using a more flexible concept of transformations between labelled graphs. of path/plan refinement without backtracking to the abstract We also proposed a number of properties to describe and clas- level. Partial solutions to capturing this concept have been sify such transformations. This framework enabled the mod- presented in the literature, for instance, the ordered mono- elling of a number of different abstraction methods in a way tonicity criterion by Knoblock, Tenenberg, and Yang (1991), that facilitated comparative analyses. It is of particular inter- the downward refinement property (DRP) by Bacchus and est that these properties can be used to capture the concept of Yang (1994), and the simulation-based approach by Bundy refinement without backtracking between levels; how to do et al. (1996). However, how to define general conditions this has been an open question for at least twenty years. -
On the Density of a Graph and Its Blowup
On the Density of a Graph and its Blowup Asaf Shapira ¤ Raphael Yustery Abstract It is well-known that, of all graphs with edge-density p, the random graph G(n; p) contains the smallest density of copies of Kt;t, the complete bipartite graph of size 2t. Since Kt;t is a t-blowup of an edge, the following intriguing open question arises: Is it true that of all graphs with triangle 3 density p , the random graph G(n; p) contains close to the smallest density of Kt;t;t, which is the t-blowup of a triangle? Our main result gives an indication that the answer to the above question is positive by showing that for some blowup, the answer must be positive. More formally we prove that if G 3 has triangle density p , then there is some 2 · t · T (p) for which the density of Kt;t;t in G is at (3+o(1))t2 least p , which (up to the o(1) term) equals the density of Kt;t;t in G(n; p). We also raise several open problems related to these problems and discuss some applications to other areas. 1 Introduction One of the main family of problems studied in extremal graph theory is how does the lack and/or number of copies of one graph H in a graph G a®ect the lack and/or number of copies of another graph H0 in G. Perhaps the most well known problems of this type are Ramsey's Theorem and Tur¶an'sTheorem. -
Implicit Structures for Graph Neural Networks
Implicit Structures for Graph Neural Networks Fangda Gu Electrical Engineering and Computer Sciences University of California at Berkeley Technical Report No. UCB/EECS-2020-185 http://www2.eecs.berkeley.edu/Pubs/TechRpts/2020/EECS-2020-185.html November 23, 2020 Copyright © 2020, by the author(s). All rights reserved. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission. Acknowledgement I would like to express my most sincere gratitude to Professor Laurent El Ghaoui and Professor Somayeh Sojoudi for their support in my academic life. The helpful discussions with them on my research have guided me through the past two successful years at University of California, Berkeley. I want to thank Heng Chang and Professor Wenwu Zhu for their help in the implementation and verification of the work. I also want to thank Shirley Salanio for her strong logistical and psychological support. Implicit Structures for Graph Neural Networks by Fangda Gu Research Project Submitted to the Department of Electrical Engineering and Computer Sciences, University of California at Berkeley, in partial satisfaction of the requirements for the degree of Master of Science, Plan II. Approval for the Report and Comprehensive Examination: Committee: Professor Laurent El Ghaoui Research Advisor (Date) * * * * * * * Professor Somayeh Sojoudi Second Reader 11/19/2020 (Date) Implicit Structures for Graph Neural Networks Fangda Gu Abstract Graph Neural Networks (GNNs) are widely used deep learning models that learn meaningful representations from graph-structured data. -
Large-Scale Directed Model Checking LTL
Large-Scale Directed Model Checking LTL Stefan Edelkamp and Shahid Jabbar University of Dortmund Otto-Hahn Straße 14 {stefan.edelkamp,shahid.jabbar}@cs.uni-dortmund.de Abstract. To analyze larger models for explicit-state model checking, directed model checking applies error-guided search, external model check- ing uses secondary storage media, and distributed model checking exploits parallel exploration on multiple processors. In this paper we propose an external, distributed and directed on-the-fly model checking algorithm to check general LTL properties in the model checker SPIN. Previous attempts restricted to checking safety proper- ties. The worst-case I/O complexity is bounded by O(sort(|F||R|)/p + l · scan(|F||S|)), where S and R are the sets of visited states and transitions in the synchronized product of the B¨uchi automata for the model and the property specification, F is the number of accepting states, l is the length of the shortest counterexample, and p is the number of processors. The algorithm we propose returns minimal lasso-shaped counterexam- ples and includes refinements for property-driven exploration. 1 Introduction The core limitation to the exploration of systems are bounded main memory resources. Relying on virtual memory slows down the exploration due to excessive page faults. External algorithms [31] exploit hard disk space and organize the access to secondary memory. Originally designed for explicit graphs, external search algorithms have shown considerably good performances in the large-scale breadth-first and guided exploration of games [22, 12] and in the analysis of model checking problems [24]. Directed explicit-state model checking [13] enhances the error-reporting capa- bilities of model checkers. -
Closest 4-Leaf Power Is Fixed-Parameter Tractable$
Discrete Applied Mathematics 156 (2008) 3345–3361 www.elsevier.com/locate/dam Closest 4-leaf power is fixed-parameter tractableI Michael Dom∗, Jiong Guo, Falk Huffner,¨ Rolf Niedermeier Institut fur¨ Informatik, Friedrich-Schiller-Universitat¨ Jena, Ernst-Abbe-Platz 2, D-07743 Jena, Germany Received 3 August 2006; received in revised form 18 December 2007; accepted 9 January 2008 Available online 4 March 2008 Abstract The NP-complete CLOSEST 4-LEAF POWER problem asks, given an undirected graph, whether it can be modified by at most r edge insertions or deletions such that it becomes a 4-leaf power. Herein, a 4-leaf power is a graph that can be constructed by considering an unrooted tree—the 4-leaf root—with leaves one-to-one labeled by the graph vertices, where we connect two graph vertices by an edge iff their corresponding leaves are at distance at most 4 in the tree. Complementing previous work on CLOSEST 2-LEAF POWER and CLOSEST 3-LEAF POWER, we give the first algorithmic result for CLOSEST 4-LEAF POWER, showing that CLOSEST 4-LEAF POWER is fixed-parameter tractable with respect to the parameter r. c 2008 Elsevier B.V. All rights reserved. Keywords: Fixed-parameter tractability; Graph algorithm; Graph modification; Graph power; Leaf power; Forbidden subgraph characterization 1. Introduction Graph powers form a classical concept in graph theory, and the rich literature dates back to the sixties of the previous century (see [5, Section 10.6] and [27] for surveys). The k-power of an undirected graph G D .V; E/ is the undirected graph Gk D .V; E0/ with .u; v/ 2 E0 iff there is a path of length at most k between u and v in G. -
Graph Powers: Hardness Results, Good Characterizations and Efficient Algorithms
Graph Powers: Hardness Results, Good Characterizations and Efficient Algorithms Dissertation zur Erlangung des akademischen Grades Doktor-Ingenieur (Dr.-Ing.) der Fakult¨at f¨ur Informatik und Elektrotechnik der Universit¨at Rostock Vorgelegt von MSc. Ngoc Tuy Nguyen Rostock, November 2009 Gutachter: Prof. Dr. Van Bang Le Universit¨at Rostock. Institut fu¨rInformatik Gutachter: Prof. Dr. Egon Wanke Heinrich- Heine- Universit¨at D¨usseldorf. Institut fu¨rInformatik Gutachter: Prof. Dr. Ekkehard K¨ohler Brandenburgische Technische Universit¨at Cottbus. Institut fu¨rMathematik Tag der ¨offentlichen Verteidigung: 30. Oktober 2009 ii Abstract Given a graph H =(VH , EH ) and a positive integer k, the k-th power of H, written Hk, is the graph obtained from H by adding new edges between any pair of vertices k at distance at most k in H; formally, H =(VH , {xy | 1 ≤ dH (x, y) ≤ k}). A graph G is the k-th power of a graph H if G = Hk, and in this case, H is a k-th root of G. For the cases of k = 2 and k = 3, we say that H2 and H3 is the square, respectively, the cube of H and H is a square root of G = H2, respectively, a cube root of G = H3. In this thesis we study the computational complexity for recognizing k-th pow- ers of general graphs as well as restricted graphs. This work provides new NP- completeness results, good characterizations and efficient algorithms for graph pow- ers. The main results are the following. • There exist reductions proving the NP-completeness for recognizing k-th pow- ers of general graphs for fixed k ≥ 2, recognizing k-th powers of bipartite graphs for fixed k ≥ 3, recognizing k-th powers of chordal graphs, and finding k-th roots of chordal graphs for all fixed k ≥ 2. -
Shorter Implicit Representation for Planar Graphs and Bounded Treewidth Graphs
Shorter Implicit Representation for Planar Graphs and Bounded Treewidth Graphs Cyril Gavoille and Arnaud Labourel LaBRI, Universit´e de Bordeaux, France {gavoille,labourel}@labri.fr Abstract. Implicit representation of graphs is a coding of the structure of graphs using distinct labels so that adjacency between any two vertices can be decided by inspecting their labels alone. All previous implicit rep- resentations of planar graphs were based on the classical three forests de- composition technique (a.k.a. Schnyder’s trees), yielding asymptotically toa3logn-bit1 label representation where n is the number of vertices of the graph. We propose a new implicit representation of planar graphs using asymptotically 2 log n-bit labels. As a byproduct we have an explicit construction of a graph with n2+o(1) vertices containing all n-vertex pla- nar graphs as induced subgraph, the best previous size of such induced- universal graph was O(n3). More generally, for graphs excluding a fixed minor, we construct a 2logn + O(log log n) implicit representation. For treewidth-k graphs we give a log n + O(k log log(n/k)) implicit representation, improving the O(k log n) representation of Kannan, Naor and Rudich [18] (STOC ’88). Our representations for planar and treewidth-k graphs are easy to implement, all the labels can be constructed in O(n log n)time,and support constant time adjacency testing. 1 Introduction How to represent a graph in memory is a basic and fundamental data structure question. The two basic ways are adjacency matrices and adjacency lists. The latter representation is space efficient for sparse graphs, but adjacency queries require searching in the list, whereas matrices allow fast queries to the price of a super-linear space. -
Recognition of C4-Free and 1/2-Hyperbolic Graphs David Coudert, Guillaume Ducoffe
Recognition of C4-free and 1/2-hyperbolic graphs David Coudert, Guillaume Ducoffe To cite this version: David Coudert, Guillaume Ducoffe. Recognition of C4-free and 1/2-hyperbolic graphs. SIAM Journal on Discrete Mathematics, Society for Industrial and Applied Mathematics, 2014, 28 (3), pp.1601-1617. 10.1137/140954787. hal-01070768 HAL Id: hal-01070768 https://hal.inria.fr/hal-01070768 Submitted on 2 Oct 2014 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. ∗ Recognition of C4-free and 1/2-hyperbolic graphs David Coudert†‡ Guillaume Ducoffe†‡§ October 2, 2014 Abstract The shortest-path metric d of a connected graph G is 1/2-hyperbolic if, and only if, it satisfies d(u,v) + d(x,y) ≤ max{d(u,x) + d(v,y), d(u,y) + d(v,x)} + 1, for every 4-tuple u,x,v,y of G. We show that the problem of deciding whether an unweighted graph is 1/2-hyperbolic is subcubic equivalent to the problem of determining whether there is a chordless cycle of length 4 in a graph. An improved algorithm is also given for both problems, taking advantage of fast rectangular matrix multiplication. -
Global Discharging Methods for Coloring Problems in Graphs Marthe Bonamy
Global discharging methods for coloring problems in graphs Marthe Bonamy To cite this version: Marthe Bonamy. Global discharging methods for coloring problems in graphs. Discrete Mathematics [cs.DM]. Université de Montpellier, 2015. English. tel-02083632 HAL Id: tel-02083632 https://tel.archives-ouvertes.fr/tel-02083632 Submitted on 29 Mar 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Délivré par l’Université Montpellier Préparée au sein de l’école doctorale I2S Et de l’unité de recherche LIRMM Spécialité: INFORMATIQUE Présentée par Marthe Bonamy Global discharging methods for coloring problems in graphs Soutenue le 9 Février 2015 devant le jury composé de Rapporteur Maria CHUDNOVSKY, Professeur, Columbia University (Absente excusée) Roland DUCOURNAU, Professeur, UM2, LIRMM Examinateur Cyril GAVOILLE, Professeur, Université de Bordeaux, LaBRI Examinateur Frédéric HAVET, Directeur de Recherche, CNRS, I3S Rapporteur Dan KRÁL’, Professeur, Warwick University Rapporteur Benjamin LÉVÊQUE, Chargé de Recherche, CNRS, LIRMM Directeur Alexandre PINLOU, Maître de Conférences, UM3, LIRMM Directeur Présidé par Frédéric HAVET. Contents Quelques mots de français 5 Introduction 10 A few words on graph coloring . 11 Global picture . 13 1 Preliminaries 15 1.1 Basic introduction to graphs and coloring . -
Mim-Width III. Graph Powers and Generalized Distance Domination Problems∗
Mim-Width III. Graph Powers and Generalized Distance Domination Problems∗ Lars Jaffkey1, O-joung Kwonz2,3, Torstein J. F. Strømme1, and Jan Arne Telle1 1Department of Informatics, University of Bergen, Norway. flars.jaffke, torstein.stromme, [email protected] 2Department of Mathematics, Incheon National University, South Korea. 3Discrete Mathematics Group, Institute for Basic Science (IBS), Daejeon, South Korea. [email protected] September 4, 2019 Abstract We generalize the family of (σ; ρ) problems and locally checkable vertex partition problems to their distance versions, which naturally captures well-known problems such as Distance-r Dominating Set and Distance-r Independent Set. We show that these distance problems are in XP parameterized by the structural parameter mim-width, and hence polynomial-time solvable on graph classes where mim-width is bounded and quickly computable, such as k- trapezoid graphs, Dilworth k-graphs, (circular) permutation graphs, interval graphs and their complements, convex graphs and their complements, k-polygon graphs, circular arc graphs, complements of d-degenerate graphs, and H-graphs if given an H-representation. We obtain these results by showing that taking any power of a graph never increases its mim-width by more than a factor of two. To supplement these findings, we show that many classes of (σ; ρ) problems are W[1]-hard parameterized by mim-width + solution size. We show that powers of graphs of tree-width w − 1 or path-width w and powers of graphs of clique-width w have mim-width at most w. These results provide new classes of bounded mim-width. We prove a slight strengthening of the first statement which implies that, surprisingly, Leaf Power graphs which are of importance in the field of phylogenetic studies have mim-width at most 1. -
Parameterized Leaf Power Recognition Via Embedding Into Graph Products
Parameterized Leaf Power Recognition via Embedding into Graph Products David Eppstein1 Computer Science Department, University of California, Irvine, USA [email protected] Elham Havvaei Computer Science Department, University of California, Irvine, USA [email protected] Abstract The k-leaf power graph G of a tree T is a graph whose vertices are the leaves of T and whose edges connect pairs of leaves at unweighted distance at most k in T . Recognition of the k-leaf power graphs for k ≥ 7 is still an open problem. In this paper, we provide two algorithms for this problem for sparse leaf power graphs. Our results shows that the problem of recognizing these graphs is fixed-parameter tractable when parameterized both by k and by the degeneracy of the given graph. To prove this, we first describe how to embed a leaf root of a leaf power graph into a product of the graph with a cycle graph. We bound the treewidth of the resulting product in terms of k and the degeneracy of G. The first presented algorithm uses methods based on monadic second-order logic (MSO2) to recognize the existence of a leaf power as a subgraph of the graph product. Using the same embedding in the graph product, the second algorithm presents a dynamic programming approach to solve the problem and provide a better dependence on the parameters. Keywords and phrases leaf power, phylogenetic tree, monadic second-order logic, Courcelle’s theorem, strong product of graphs, fixed-parameter tractability, dynamic programming, tree decomposition 1 Introduction Leaf powers are a class of graphs that were introduced in 2002 by Nishimura, Ragde and Thilikos [41], extending the notion of graph powers.