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We address the question of whether it may be worthwhile to convert certain, now classical, NP-complete problems to one of a smaller number of kernel NP-complete problems. In particular, we show that Karp's classical set of 21 NP-complete…

Combinatorics · Mathematics 2019-02-28 Jerzy A Filar , Michael Haythorpe , Richard Taylor

The composition technique is a popular method for excluding polynomial-size problem kernels for NP-hard parameterized problems. We present a new technique exploiting triangle-based fractal structures for extending the range of applicability…

Computational Complexity · Computer Science 2017-12-27 Till Fluschnik , Danny Hermelin , André Nichterlein , Rolf Niedermeier

For a fixed simple digraph $H$ without isolated vertices, we consider the problem of deleting arcs from a given tournament to get a digraph which does not contain $H$ as an immersion. We prove that for every $H$, this problem admits a…

Data Structures and Algorithms · Computer Science 2022-08-17 Łukasz Bożyk , Michał Pilipczuk

In the \textsc{Subset Feedback Vertex Set (Subset-FVS)} problem the input is a graph $G$, a subset \(T\) of vertices of \(G\) called the `terminal' vertices, and an integer $k$. The task is to determine whether there exists a subset of…

Data Structures and Algorithms · Computer Science 2019-01-09 Geevarghese Philip , Varun Rajan , Saket Saurabh , Prafullkumar Tale

Vertex deletion and edge deletion problems play a central role in Parameterized Complexity. Examples include classical problems like Feedback Vertex Set, Odd Cycle Transversal, and Chordal Deletion. Interestingly, the study of edge…

Data Structures and Algorithms · Computer Science 2011-04-20 Pinar Heggernes , Pim van 't Hof , Benjamin Lévêque , Daniel Lokshtanov , Christophe Paul

A graph G=(V,E) is a 3-leaf power iff there exists a tree T whose leaves are V and such that (u,v) is an edge iff u and v are at distance at most 3 in T. The 3-leaf power graph edge modification problems, i.e. edition (also known as the…

Discrete Mathematics · Computer Science 2015-05-13 Stephane Bessy , Christophe Paul , Anthony Perez

Graph kernels have been successfully applied to many graph classification problems. Typically, a kernel is first designed, and then an SVM classifier is trained based on the features defined implicitly by this kernel. This two-stage…

Many scientific problems require identifying a small set of covariates that are associated with a target response and estimating their effects. Often, these effects are nonlinear and include interactions, so linear and additive methods can…

Computation · Statistics 2022-12-02 Raj Agrawal , Tamara Broderick

In the Selective Coloring problem, we are given an integer $k$, a graph $G$, and a partition of $V(G)$ into $p$ parts, and the goal is to decide whether or not we can pick exactly one vertex of each part and obtain a $k$-colorable induced…

Data Structures and Algorithms · Computer Science 2020-12-01 Guilherme C. M. Gomes , Vinicius F. dos Santos

Neural kernels have drastically increased performance on diverse and nonstandard data modalities but require significantly more compute, which previously limited their application to smaller datasets. In this work, we address this by…

Machine Learning · Statistics 2023-03-10 Ben Adlam , Jaehoon Lee , Shreyas Padhy , Zachary Nado , Jasper Snoek

Parallel fixed-parameter tractability studies how parameterized problems can be solved in parallel. A surprisingly large number of parameterized problems admit a high level of parallelization, but this does not mean that we can also…

Computational Complexity · Computer Science 2018-07-11 Max Bannach , Till Tantau

For many problems, the important instances from practice possess certain structure that one should reflect in the design of specific algorithms. As data reduction is an important and inextricable part of today's computation, we employ one…

Data Structures and Algorithms · Computer Science 2022-07-05 Václav Blažej , Pratibha Choudhary , Dušan Knop , Šimon Schierreich , Ondřej Suchý , Tomáš Valla

Let $G$ be a planar graph and $I_s$ and $I_t$ be two independent sets in $G$, each of size $k$. We begin with a "token" on each vertex of $I_s$ and seek to move all tokens to $I_t$, by repeated "token jumping", removing a single token from…

Discrete Mathematics · Computer Science 2024-08-14 Daniel W. Cranston

In the solution discovery problem for a search problem on graphs, we are given an initial placement of $k$ tokens on the vertices of a graph and asked whether this placement can be transformed into a feasible solution by applying a small…

Data Structures and Algorithms · Computer Science 2025-12-01 Rin Saito , Anouk Sommer , Tatsuhiro Suga , Takahiro Suzuki , Yuma Tamura

We investigate the parameterized complexity of the graph editing problem called Editing to a Graph with a Given Degree Sequence, where the aim is to obtain a graph with a given degree sequence \sigma by at most k vertex or edge deletions…

Data Structures and Algorithms · Computer Science 2016-01-14 Petr A. Golovach , George B. Mertzios

Kernelization algorithms are polynomial-time reductions from a problem to itself that guarantee their output to have a size not exceeding some bound. For example, d-Set Matching for integers d>2 is the problem of finding a matching of size…

Data Structures and Algorithms · Computer Science 2018-12-10 Holger Dell , Dániel Marx

Connectivity problems like k-Path and k-Disjoint Paths relate to many important milestones in parameterized complexity, namely the Graph Minors Project, color coding, and the recent development of techniques for obtaining kernelization…

Data Structures and Algorithms · Computer Science 2015-03-19 Hans L. Bodlaender , Bart M. P. Jansen , Stefan Kratsch

In the F-minor-free deletion problem we want to find a minimum vertex set in a given graph that intersects all minor models of graphs from the family F. The Vertex planarization problem is a special case of F-minor-free deletion for the…

Data Structures and Algorithms · Computer Science 2022-02-07 Bart M. P. Jansen , Michał Włodarczyk

Many deep neural networks are built by using stacked convolutional layers of fixed and single size (often 3$\times$3) kernels. This paper describes a method for training the size of convolutional kernels to provide varying size kernels in a…

Computer Vision and Pattern Recognition · Computer Science 2020-09-15 F. Boray Tek , İlker Çam , Deniz Karlı

A graph H is a square root of a graph G if G can be obtained from H by the addition of edges between any two vertices in H that are of distance 2 from each other. The Square Root problem is that of deciding whether a given graph admits a…

Data Structures and Algorithms · Computer Science 2016-08-23 Petr A. Golovach , Dieter Kratsch , Daniël Paulusma , Anthony Stewart
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