404 research outputs found
Tree-edges deletion problems with bounded diameter obstruction sets
AbstractWe study the following problem: given a tree G and a finite set of trees H, find a subset O of the edges of G such that G-O does not contain a subtree isomorphic to a tree from H, and O has minimum cardinality. We give sharp boundaries on the tractability of this problem: the problem is polynomial when all the trees in H have diameter at most 5, while it is NP-hard when all the trees in H have diameter at most 6. We also show that the problem is polynomial when every tree in H has at most one vertex with degree more than 2, while it is NP-hard when the trees in H can have two such vertices.The polynomial-time algorithms use a variation of a known technique for solving graph problems. While the standard technique is based on defining an equivalence relation on graphs, we define a quasiorder. This new variation might be useful for giving more efficient algorithm for other graph problems
Fast Biclustering by Dual Parameterization
We study two clustering problems, Starforest Editing, the problem of adding
and deleting edges to obtain a disjoint union of stars, and the generalization
Bicluster Editing. We show that, in addition to being NP-hard, none of the
problems can be solved in subexponential time unless the exponential time
hypothesis fails.
Misra, Panolan, and Saurabh (MFCS 2013) argue that introducing a bound on the
number of connected components in the solution should not make the problem
easier: In particular, they argue that the subexponential time algorithm for
editing to a fixed number of clusters (p-Cluster Editing) by Fomin et al. (J.
Comput. Syst. Sci., 80(7) 2014) is an exception rather than the rule. Here, p
is a secondary parameter, bounding the number of components in the solution.
However, upon bounding the number of stars or bicliques in the solution, we
obtain algorithms which run in time for p-Starforest
Editing and for p-Bicluster Editing. We
obtain a similar result for the more general case of t-Partite p-Cluster
Editing. This is subexponential in k for fixed number of clusters, since p is
then considered a constant.
Our results even out the number of multivariate subexponential time
algorithms and give reasons to believe that this area warrants further study.Comment: Accepted for presentation at IPEC 201
Obstructions to weak decomposability for simplicial polytopes
Provan and Billera introduced notions of (weak) decomposability of simplicial
complexes as a means of attempting to prove polynomial upper bounds on the
diameter of the facet-ridge graph of a simplicial polytope. Recently, De Loera
and Klee provided the first examples of simplicial polytopes that are not
weakly vertex-decomposable. These polytopes are polar to certain simple
transportation polytopes. In this paper, we refine their analysis to prove that
these -dimensional polytopes are not even weakly -decomposable.
As a consequence, (weak) decomposability cannot be used to prove a polynomial
version of the Hirsch conjecture
Meta-Kernelization using Well-Structured Modulators
Kernelization investigates exact preprocessing algorithms with performance
guarantees. The most prevalent type of parameters used in kernelization is the
solution size for optimization problems; however, also structural parameters
have been successfully used to obtain polynomial kernels for a wide range of
problems. Many of these parameters can be defined as the size of a smallest
modulator of the given graph into a fixed graph class (i.e., a set of vertices
whose deletion puts the graph into the graph class). Such parameters admit the
construction of polynomial kernels even when the solution size is large or not
applicable. This work follows up on the research on meta-kernelization
frameworks in terms of structural parameters.
We develop a class of parameters which are based on a more general view on
modulators: instead of size, the parameters employ a combination of rank-width
and split decompositions to measure structure inside the modulator. This allows
us to lift kernelization results from modulator-size to more general
parameters, hence providing smaller kernels. We show (i) how such large but
well-structured modulators can be efficiently approximated, (ii) how they can
be used to obtain polynomial kernels for any graph problem expressible in
Monadic Second Order logic, and (iii) how they allow the extension of previous
results in the area of structural meta-kernelization
The Parameterized Complexity of Degree Constrained Editing Problems
This thesis examines degree constrained editing problems within the framework of parameterized complexity. A degree constrained editing problem takes as input a graph and a set of constraints and asks whether the graph can be altered in at most k editing steps such that the degrees of the remaining vertices are within the given constraints. Parameterized complexity gives a framework for examining
problems that are traditionally considered intractable and developing efficient exact algorithms for them, or showing that it is unlikely that they have such algorithms, by introducing an additional component to the input, the parameter, which gives additional information about the structure of the problem. If the problem has an algorithm that is exponential in the parameter, but polynomial, with constant degree, in the size of the input, then it is considered to be fixed-parameter tractable.
Parameterized complexity also provides an intractability framework for identifying problems that are likely to not have such an algorithm.
Degree constrained editing problems provide natural parameterizations in terms of the total cost k of vertex deletions, edge deletions and edge additions allowed, and
the upper bound r on the degree of the vertices remaining after editing. We define a class of degree constrained editing problems, WDCE, which generalises several well know problems, such as Degree r Deletion, Cubic Subgraph, r-Regular Subgraph, f-Factor and General Factor. We show that in general if both k and r are part of the parameter, problems in the WDCE class are fixed-parameter tractable, and if parameterized by k or r alone, the problems are intractable in a parameterized sense.
We further show cases of WDCE that have polynomial time kernelizations, and in particular when all the degree constraints are a single number and the editing
operations include vertex deletion and edge deletion we show that there is a kernel with at most O(kr(k + r)) vertices. If we allow vertex deletion and edge addition,
we show that despite remaining fixed-parameter tractable when parameterized by k and r together, the problems are unlikely to have polynomial sized kernelizations, or
polynomial time kernelizations of a certain form, under certain complexity theoretic assumptions.
We also examine a more general case where given an input graph the question is whether with at most k deletions the graph can be made r-degenerate. We show that in this case the problems are intractable, even when r is a constant
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