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In the Maximize Phylogenetic Diversity problem, we are given a phylogenetic tree that represents the genetic proximity of species, and we are asked to select a subset of species of maximum phylogenetic diversity to be preserved through…

Computational Complexity · Computer Science 2026-02-16 Niels Holtgrefe , Jannik Schestag , Norbert Zeh

The notion of treewidth plays an important role in theoretical and practical studies of graph problems. It has been recognized that, especially in practical environments, when computing the treewidth of a graph it is invaluable to first…

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

We extend the notion of lossy kernelization, introduced by Lokshtanov et al. [STOC 2017], to approximate Turing kernelization. An $\alpha$-approximate Turing kernel for a parameterized optimization problem is a polynomial-time algorithm…

Data Structures and Algorithms · Computer Science 2020-04-28 Eva-Maria C. Hols , Stefan Kratsch , Astrid Pieterse

Meta-theorems for polynomial (linear) kernels have been the subject of intensive research in parameterized complexity. Heretofore, meta-theorems for linear kernels exist on graphs of bounded genus, $H$-minor-free graphs, and…

We investigate polynomial-time preprocessing for the problem of hitting forbidden minors in a graph, using the framework of kernelization. For a fixed finite set of connected graphs F, the F-Deletion problem is the following: given a graph…

Computational Complexity · Computer Science 2018-04-25 Bart M. P. Jansen , Astrid Pieterse

In the framework of computational complexity and in an effort to define a more natural reduction for problems of equivalence, we investigate the recently introduced kernel reduction, a reduction that operates on each element of a pair…

Computational Complexity · Computer Science 2016-04-29 Jeffrey Finkelstein , Benjamin Hescott

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…

Data Structures and Algorithms · Computer Science 2015-07-21 Eduard Eiben , Robert Ganian , Stefan Szeider

Structural graph parameters play an important role in parameterized complexity, including in kernelization. Notably, vertex cover, neighborhood diversity, twin-cover, and modular-width have been studied extensively in the last few years.…

Computational Complexity · Computer Science 2023-06-23 Manuel Lafond , Weidong Luo

We study a general class of problems called F-deletion problems. In an F-deletion problem, we are asked whether a subset of at most $k$ vertices can be deleted from a graph $G$ such that the resulting graph does not contain as a minor any…

Data Structures and Algorithms · Computer Science 2010-10-08 Fedor V. Fomin , Daniel Lokshtanov , Neeldhara Misra , Geevarghese Philip , Saket Saurabh

Until recently, techniques for obtaining lower bounds for kernelization were one of the most sought after tools in the field of parameterized complexity. Now, after a strong influx of techniques, we are in the fortunate situation of having…

Data Structures and Algorithms · Computer Science 2015-03-19 Stefan Kratsch

The Vertex Cover problem plays an essential role in the study of polynomial kernelization in parameterized complexity, i.e., the study of provable and efficient preprocessing for NP-hard problems. Motivated by the great variety of positive…

Computational Complexity · Computer Science 2019-05-10 Eva-Maria C. Hols , Stefan Kratsch , Astrid Pieterse

We introduce the cross-composition framework for proving kernelization lower bounds. A classical problem L AND/OR-cross-composes into a parameterized problem Q if it is possible to efficiently construct an instance of Q with polynomially…

Computational Complexity · Computer Science 2015-03-20 Hans L. Bodlaender , Bart M. P. Jansen , Stefan Kratsch

The maximum stable set problem is NP-hard, even when restricted to triangle-free graphs. In particular, one cannot expect a polynomial time algorithm deciding if a bull-free graph has a stable set of size $k$, when $k$ is part of the…

Discrete Mathematics · Computer Science 2015-11-20 Stéphan Thomassé , Nicolas Trotignon , Kristina Vusković

In this paper, we study the parameterized complexity of a generalized domination problem called the [${\sigma}, {\rho}$] Dominating Set problem. This problem generalizes a large number of problems including the Minimum Dominating Set…

Computational Complexity · Computer Science 2022-11-10 Pradeesha Ashok , Rajath Rao , Avi Tomar

We study the kernelization complexity of structural parameterizations of the Vertex Cover problem. Here, the goal is to find a polynomial-time preprocessing algorithm that can reduce any instance $(G,k)$ of the Vertex Cover problem to an…

Data Structures and Algorithms · Computer Science 2023-07-25 Marin Bougeret , Bart M. P. Jansen , Ignasi Sau

The notion of Turing kernelization investigates whether a polynomial-time algorithm can solve an NP-hard problem, when it is aided by an oracle that can be queried for the answers to bounded-size subproblems. One of the main open problems…

Data Structures and Algorithms · Computer Science 2017-07-07 Bart M. P. Jansen , Marcin Pilipczuk , Marcin Wrochna

Kernelization studies polynomial-time preprocessing algorithms. Over the last 20 years, the most celebrated positive results of the field have been linear kernels for classical NP-hard graph problems on sparse graph classes. In this paper,…

Data Structures and Algorithms · Computer Science 2025-11-06 Christian Bertram , Deborah Haun , Mads Vestergaard Jensen , Tuukka Korhonen

The Workflow Satisfiability Problem (WSP) is a problem of practical interest that arises whenever tasks need to be performed by authorized users, subject to constraints defined by business rules. We are required to decide whether there…

Computational Complexity · Computer Science 2014-09-26 Gregory Gutin , Stefan Kratsch , Magnus Wahlström

Kernelization is a theoretical formalization of efficient preprocessing for NP-hard problems. Empirically, preprocessing is highly successful in practice, for example in state-of-the-art ILP-solvers like CPLEX. Motivated by this, previous…

Computational Complexity · Computer Science 2015-06-26 Bart M. P. Jansen , Stefan Kratsch

A fundamental graph problem is to recognize whether the vertex set of a graph $G$ can be bipartitioned into sets $A$ and $B$ such that $G[A]$ and $G[B]$ satisfy properties $\Pi_A$ and $\Pi_B$, respectively. This so-called…

Computational Complexity · Computer Science 2019-08-27 Iyad Kanj , Christian Komusiewicz , Manuel Sorge , Erik Jan van Leeuwen