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Meta-kernelization theorems are general results that provide polynomial kernels for large classes of parameterized problems. The known meta-kernelization theorems, in particular the results of Bodlaender et al. (FOCS'09) and of Fomin et al.…

Data Structures and Algorithms · Computer Science 2013-04-22 Robert Ganian , Friedrich Slivovsky , Stefan Szeider

Let F be a finite family of graphs. In the F-Deletion problem, one is given a graph G and an integer k, and the goal is to find k vertices whose deletion results in a graph with no minor from the family F. This may be regarded as a…

Data Structures and Algorithms · Computer Science 2026-01-21 Roohani Sharma , Michał Włodarczyk

Given a graph $G=(V,E)$ and an integer $k \ge 1$, a $k$-hop dominating set $D$ of $G$ is a subset of $V$, such that, for every vertex $v \in V$, there exists a node $u \in D$ whose hop-distance from $v$ is at most $k$. A $k$-hop dominating…

Data Structures and Algorithms · Computer Science 2020-12-11 A. Karim Abu-Affash , Paz Carmi , Adi Krasin

Enumerative kernelization is a recent and promising area sitting at the intersection of parameterized complexity and enumeration algorithms. Its study began with the paper of Creignou et al. [Theory Comput. Syst., 2017], and development in…

Data Structures and Algorithms · Computer Science 2025-09-11 Marin Bougeret , Guilherme C. M. Gomes , Vinicius F. dos Santos , Ignasi Sau

We consider (closed neighbourhood) packings and their generalization in graphs called limited packings. A vertex set X in a graph G is a k-limited packing if for any vertex $v\in V(G)$, $\left|N[v] \cap X\right| \le k$, where $N[v]$ is the…

Discrete Mathematics · Computer Science 2014-07-08 Andrei Gagarin , Vadim Zverovich

Metric and kernel learning are important in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional data, while existing kernel learning algorithms are…

Machine Learning · Computer Science 2009-11-02 Prateek Jain , Brian Kulis , Jason V. Davis , Inderjit S. Dhillon

Computing high-quality independent sets quickly is an important problem in combinatorial optimization. Several recent algorithms have shown that kernelization techniques can be used to find exact maximum independent sets in medium-sized…

Data Structures and Algorithms · Computer Science 2016-02-05 Jakob Dahlum , Sebastian Lamm , Peter Sanders , Christian Schulz , Darren Strash , Renato F. Werneck

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

We consider the parameterized complexity of the problem of tracking shortest s-t paths in graphs, motivated by applications in security and wireless networks. Given an undirected and unweighted graph with a source s and a destination t,…

Data Structures and Algorithms · Computer Science 2020-08-19 Aritra Banik , Pratibha Choudhary , Venkatesh Raman , Saket Saurabh

The three-in-a-tree problem asks for an induced tree of the input graph containing three mandatory vertices. In 2006, Chudnovsky and Seymour [Combinatorica, 2010] presented the first polynomial time algorithm for this problem, which has…

Data Structures and Algorithms · Computer Science 2020-07-10 Guilherme C. M. Gomes , Vinicius F. dos Santos , Murilo V. G. da Silva , Jayme L. Szwarcfiter

Low-rank approximation is a common tool used to accelerate kernel methods: the $n \times n$ kernel matrix $K$ is approximated via a rank-$k$ matrix $\tilde K$ which can be stored in much less space and processed more quickly. In this work…

Data Structures and Algorithms · Computer Science 2017-11-07 Cameron Musco , David P. Woodruff

An $\alpha$-approximate polynomial Turing kernelization is a polynomial-time algorithm that computes an $(\alpha c)$-approximate solution for a parameterized optimization problem when given access to an oracle that can compute…

Data Structures and Algorithms · Computer Science 2023-07-06 Stefan Kratsch , Pascal Kunz

We consider supervised learning problems within the positive-definite kernel framework, such as kernel ridge regression, kernel logistic regression or the support vector machine. With kernels leading to infinite-dimensional feature spaces,…

Machine Learning · Computer Science 2013-05-23 Francis Bach

In parameterized algorithmics, the process of kernelization is defined as a polynomial time algorithm that transforms the instance of a given problem to an equivalent instance of a size that is limited by a function of the parameter. As,…

Computational Complexity · Computer Science 2019-03-01 Jouke Witteveen , Ralph Bottesch , Leen Torenvliet

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

The main challenge addressed in this paper is to identify individual terms in a superposition of heat kernels on a graph. We establish geometric conditions on the vertices at which these heat kernels are centered and find bounds on the time…

Functional Analysis · Mathematics 2026-05-19 Bernhard G. Bodmann , Jennifer J. May

We present a method for reducing the treewidth of a graph while preserving all of its minimal $s-t$ separators up to a certain fixed size $k$. This technique allows us to solve $s-t$ Cut and Multicut problems with various additional…

Data Structures and Algorithms · Computer Science 2015-03-19 Dániel Marx , Barry O'Sullivan , Igor Razgon

In the $k$-Leaf Out-Branching and $k$-Internal Out-Branching problems we are given a directed graph $D$ with a designated root $r$ and a nonnegative integer $k$. The question is to determine the existence of an outbranching rooted at $r$…

Data Structures and Algorithms · Computer Science 2015-09-08 Marthe Bonamy , Łukasz Kowalik , Michał Pilipczuk , Arkadiusz Socała

In the Tree Deletion Set problem the input is a graph G together with an integer k. The objective is to determine whether there exists a set S of at most k vertices such that G-S is a tree. The problem is NP-complete and even NP-hard to…

Data Structures and Algorithms · Computer Science 2013-10-01 Archontia C. Giannopoulou , Daniel Lokshtanov , Saket Saurabh , Ondrej Suchy

Kernel methods obtain superb performance in terms of accuracy for various machine learning tasks since they can effectively extract nonlinear relations. However, their time complexity can be rather large especially for clustering tasks. In…

Machine Learning · Statistics 2015-10-29 Xu Wang , Gilad Lerman