Given two graphs H and G, the SUBGRAPH ISOMORPHISM problem asks if H is isomorphic to a subgraph of G. While NP-hard in general, algorithms exist for various parameterized versions of the problem. However, the literat...
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ISBN:
(纸本)9783939897651
Given two graphs H and G, the SUBGRAPH ISOMORPHISM problem asks if H is isomorphic to a subgraph of G. While NP-hard in general, algorithms exist for various parameterized versions of the problem. However, the literature contains very little guidance on which combinations of parameters can or cannot be exploited algorithmically. Our goal is to systematically investigate the possible parameterized algorithms that can exist for SUBGRAPH ISOMORPHISM. We develop a framework involving 10 relevant parameters for each of H and G (such as treewidth, pathwidth, genus, maximum degree, number of vertices, number of components, etc.), and ask if an algorithm with running time ft (p(1),p(2), ..., p(l)) . n(f2(pl+1, ..., pk)) exists, where each of p(1), ..., p(k) is one of the 10 parameters depending only on H or G. We show that all the questions arising in this framework are answered by a set of 11 maximal positive results (algorithms) and a set of 17 maximal negative results (hardness proofs);some of these results already appear in the literature, while others are new in this paper. On the algorithmic side, our study reveals for example that an unexpected combination of bounded degree, genus, and feedback vertex set number of G gives rise to a highly nontrivial algorithm for SUBGRAPH ISOMORPHISM. On the hardness side, we present W[1]-hardness proofs under extremely restricted conditions, such as when H is a bounded-degree tree of constant pathwidth and G is a planar graph of bounded pathwidth.
The problem MAX W-LIGHT (MAX W-HEAVY) for an undirected graph is to assign a direction to each edge so that the number of vertices of outdegree at most W (resp. at least W) is maximized. It is known that these problem...
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ISBN:
(纸本)9783959770262
The problem MAX W-LIGHT (MAX W-HEAVY) for an undirected graph is to assign a direction to each edge so that the number of vertices of outdegree at most W (resp. at least W) is maximized. It is known that these problems are NP-hard even for fixed W. For example, MAX 0- LIGHT is equivalent to the problem of finding a maximum independent set. In this paper, we show that for any fixed constant W, MAX W-HEAVY can be solved in linear time for hereditary graph classes for which treewidth is bounded by a function of degeneracy. We show that such graph classes include chordal graphs, circular-arc graphs, d-trapezoid graphs, chordal bipartite graphs, and graphs of bounded clique-width. To have a polynomial-time algorithm for MAX W-LIGHT, we need an additional condition of a polynomial upper bound on the number of potential maximal cliques to apply the metatheorem by Fomin et al. (SIAM J Comput 44:54-87, 2015). The aforementioned graph classes, except bounded clique-width graphs, satisfy such a condition. For graphs of bounded clique-width, we present a dynamic programming approach not using the metatheorem to show that it is actually polynomial-time solvable for this graph class too. We also study the parameterized complexity of the problems and show some tractability and intractability results.
We analyse the complexity of learning first-order queries in a model-theoretic framework for supervised learning introduced by (Grohe and Turan, TOCS 2004). Previous research on the complexity of learning in this fram...
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ISBN:
(纸本)9781450392600
We analyse the complexity of learning first-order queries in a model-theoretic framework for supervised learning introduced by (Grohe and Turan, TOCS 2004). Previous research on the complexity of learning in this framework focussed on the question of when learning is possible in time sublinear in the background structure. Here we study the parameterized complexity of the learning problem. We have two main results. The first is a hardness result, showing that learning first-order queries is at least as hard as the corresponding model-checking problem, which implies that on general structures it is hard for the parameterized complexity class AW[*]. Our second main contribution is a fixed-parameter tractable agnostic PAC learning algorithm for first-order queries over sparse relational data (more precisely, over nowhere dense background structures).
The rigidity of a matrix A for a target rank r over a field IF is the minimum Hamming distance between A and a matrix of rank at most r. Rigidity is a classical concept in Computational complexity Theory: construction...
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ISBN:
(纸本)9783959770286
The rigidity of a matrix A for a target rank r over a field IF is the minimum Hamming distance between A and a matrix of rank at most r. Rigidity is a classical concept in Computational complexity Theory: constructions of rigid matrices are known to imply lower bounds of significant importance relating to arithmetic circuits. Yet, from the viewpoint of parameterized complexity, the study of central properties of matrices in general, and of the rigidity of a matrix in particular, has been neglected. In this paper, we conduct a comprehensive study of different aspects of the computation of the rigidity of general matrices in the framework of parameterized complexity. Naturally, given parameters r and k, the MATRIX RIGIDITY problem asks whether the rigidity of A for the target rank r is at most k. We show that in case F = R or F is any finite field, this problem is fixed-parameter tractable with respect to k + r. To this end, we present a dimension reduction procedure, which may be a valuable primitive in future studies of problems of this nature. We also employ central tools in Real Algebraic Geometry, which are not well known in parameterized complexity, as a black box. In particular, we view the output of our dimension reduction procedure as an algebraic variety. Our main results are complemented by a W[1]-hardness result and a subexponential-time parameterized algorithm for a special case of MATRIX RIGIDITY, highlighting the different flavors of this problem.
Computing planar orthogonal drawings with the minimum number of bends is one of the most relevant topics in Graph Drawing. The problem is known to be NP-hard, even when we want to test the existence of a rectilinear p...
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ISBN:
(纸本)9783031492747;9783031492754
Computing planar orthogonal drawings with the minimum number of bends is one of the most relevant topics in Graph Drawing. The problem is known to be NP-hard, even when we want to test the existence of a rectilinear planar drawing, i.e., an orthogonal drawing without bends (Garg and Tamassia, 2001). From the parameterized complexity perspective, the problem is fixed-parameter tractable when parameterized by the sum of three parameters: the number of bends, the number of vertices of degree at most two, and the treewidth of the input graph (Di Giacomo et al., 2022). We improve this last result by showing that the problem remains fixed-parameter tractable when parameterized only by the number of vertices of degree at most two plus the number of bends. As a consequence, rectilinear planarity testing lies in FPT parameterized by the number of vertices of degree at most two.
We study the parameterized complexity of the following fundamental geometric problems with respect to the dimension d: i) Given n points in R-d, compute their minimum enclosing cylinder. ii) Given two n-point sets in ...
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ISBN:
(纸本)9783642112683
We study the parameterized complexity of the following fundamental geometric problems with respect to the dimension d: i) Given n points in R-d, compute their minimum enclosing cylinder. ii) Given two n-point sets in Rd, decide whether they can be separated by two hyperplanes. iii) Given a system of n linear inequalities with d variables, find a maximum size feasible subsystem. We show that (the decision versions of) all these problems are W[1]-hard when parameterized by the dimension d. Our reductions also give n(Omega(d))-time lower bound (under the Exponential Time Hypothesis).
In this paper, we investigate the parameterized complexity of d-restricted tau-synthesis (dR tau S) parameterized by d for a range of Boolean types of nets tau. We show that dR tau S is W[1]-hard for 64 of 128 possibl...
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ISBN:
(纸本)9783030592660;9783030592677
In this paper, we investigate the parameterized complexity of d-restricted tau-synthesis (dR tau S) parameterized by d for a range of Boolean types of nets tau. We show that dR tau S is W[1]-hard for 64 of 128 possible Boolean types that allow places and transitions to be independent.
In Group Activity Selection Problem with graph structure (gGASP), players form coalitions to participate in activities and have preferences over pairs of the form (activity, group size);moreover, a group of players ca...
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ISBN:
(纸本)9781510855076
In Group Activity Selection Problem with graph structure (gGASP), players form coalitions to participate in activities and have preferences over pairs of the form (activity, group size);moreover, a group of players can only engage in the same activity if the members of the group form a connected subset of the underlying communication structure. We study the parameterized complexity of finding outcomes of gGASP that are Nash stable, individually stable or core stable. For the parameter 'number of activities', we propose an FPT algorithm for Nash stability for the case where the social network is acyclic and obtain a W[1]-hardness result for cliques (i.e., for classic GASP);similar results hold for individual stability. In contrast, finding a core stable outcome is hard even if the number of activities is bounded by a small constant, both for classic GASP and when the social network is a star. For the parameter 'number of players', all problems we consider are in XP for arbitrary social networks;on the other hand, we prove W[1]-hardness results with respect to the parameter 'number of players' for the case where the social network is a clique (i.e., for classic GASP).
A graph G = (V, E) is called equidominating if there exists a value t is an element of IN and a weight function omega: V -> IN such that the total weight of a subset D subset of V is equal to t if and only if D is ...
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ISBN:
(纸本)9783319687056;9783319687049
A graph G = (V, E) is called equidominating if there exists a value t is an element of IN and a weight function omega: V -> IN such that the total weight of a subset D subset of V is equal to t if and only if D is a minimal dominating set. To decide whether or not a given graph is equidominating is referred to as the EQUIDOMINATION problem. In this paper we show that two parameterized versions of the EQUIDOMINATION problem are fixed-parameter tractable: the first parameterization considers the target value t leading to the TARGET- t EQUIDOMINATION problem. The second parameterization allows only weights up to a value k, which yields the k- EQUIDOMINATION problem. In addition, we characterize the graphs whose every induced subgraph is equidominating. We give a finite forbidden induced subgraph characterization and derive a fast recognition algorithm.
In our previous work we introduced Partition sort and found it to be more robust compared to the Quick sort in average case. This paper does a more comprehensive comparative study of the relative performance of these ...
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ISBN:
(纸本)9783642315510
In our previous work we introduced Partition sort and found it to be more robust compared to the Quick sort in average case. This paper does a more comprehensive comparative study of the relative performance of these two algorithms with focus on parameterized complexity analysis. The empirical results revealed that Partition sort is the better choice for discrete distribution inputs, whereas Quick sort was found to have a clear edge for continuous data sets.
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