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In this paper we propose a new non-linear classifier based on a combination of locally linear classifiers. A well known optimization formulation is given as we cast the problem in a $\ell_1$ Multiple Kernel Learning (MKL) problem using many…

Machine Learning · Computer Science 2024-01-19 David Picard

We study extensions of the classic \emph{Line Cover} problem, which asks whether a set of $n$ points in the plane can be covered using $k$ lines. Line Cover is known to be NP-hard, and we focus on two natural generalizations. The first is…

Computational Geometry · Computer Science 2026-03-26 Matthias Bentert , Fedor v. Fomin , Petr A. Golovach , Souvik Saha , Sanjay Seetharaman , Kirill Simonov , Anannya Upasana

We consider the problem of discovering overlapping communities in networks which we model as generalizations of Graph Packing problems with overlap. We seek a collection $\mathcal{S}' \subseteq \mathcal{S}$ consisting of at least $k$ sets…

Data Structures and Algorithms · Computer Science 2015-01-27 Henning Fernau , Alejandro López-Ortiz , Jazmín Romero

Many graph problems were first shown to be fixed-parameter tractable using the results of Robertson and Seymour on graph minors. We show that the combination of finite, computable, obstruction sets and efficient order tests is not just one…

Computational Complexity · Computer Science 2013-05-15 Michael R. Fellows , Bart M. P. Jansen

Many algorithms have been developed for NP-hard problems on graphs with small treewidth $k$. For example, all problems that are expressable in linear extended monadic second order can be solved in linear time on graphs of bounded treewidth.…

Data Structures and Algorithms · Computer Science 2016-05-17 Frank Kammer , Torsten Tholey

We propose a preprocessing algorithm for the multiway cut problem that establishes its polynomial kernelizability when the difference between the parameter $k$ and the size of the smallest isolating cut is at most $log(k)$. To the best of…

Discrete Mathematics · Computer Science 2011-05-03 Igor Razgon

We present a novel framework for kernel learning with sequential data of any kind, such as time series, sequences of graphs, or strings. Our approach is based on signature features which can be seen as an ordered variant of sample…

Machine Learning · Statistics 2016-02-01 Franz J Király , Harald Oberhauser

We consider (closed neighbourhood) packings and their generalization in graphs. 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 closed neighbourhood of v.…

Discrete Mathematics · Computer Science 2015-05-18 Andrei Gagarin , Vadim Zverovich

In the Vertex Cover problem we are given a graph $G=(V,E)$ and an integer $k$ and have to determine whether there is a set $X\subseteq V$ of size at most $k$ such that each edge in $E$ has at least one endpoint in $X$. The problem can be…

Data Structures and Algorithms · Computer Science 2016-11-22 Stefan Kratsch

We study the fair k-set selection problem where we aim to select $k$ sets from a given set system such that the (weighted) occurrence times that each element appears in these $k$ selected sets are balanced, i.e., the maximum (weighted)…

Data Structures and Algorithms · Computer Science 2025-05-20 Shi Li , Chenyang Xu , Ruilong Zhang

We propose a new technique for constructing low-rank approximations of matrices that arise in kernel methods for machine learning. Our approach pairs a novel automatically constructed analytic expansion of the underlying kernel function…

Machine Learning · Computer Science 2022-02-09 John Paul Ryan , Anil Damle

We study the existence of polynomial kernels, for parameterized problems without a polynomial kernel on general graphs, when restricted to graphs of bounded twin-width. Our main result is that a polynomial kernel for $k$-Dominating Set on…

Data Structures and Algorithms · Computer Science 2021-09-15 Édouard Bonnet , Eun Jung Kim , Amadeus Reinald , Stéphan Thomassé , Rémi Watrigant

Kernel matrices appear in machine learning and non-parametric statistics. Given $N$ points in $d$ dimensions and a kernel function that requires $\mathcal{O}(d)$ work to evaluate, we present an $\mathcal{O}(dN\log N)$-work algorithm for the…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-01-11 Chenhan D. Yu , William B. March , George Biros

We study the kernelization of exploration problems on temporal graphs. A temporal graph consists of a finite sequence of snapshot graphs $\mathcal{G}=(G_1, G_2, \dots, G_L)$ that share a common vertex set but might have different edge sets.…

Computational Complexity · Computer Science 2023-02-21 Emmanuel Arrighi , Fedor V. Fomin , Petr Golovach , Petra Wolf

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

A stable cutset in a graph $G$ is a set $S\subseteq V(G)$ such that vertices of $S$ are pairwise non-adjacent and such that $G-S$ is disconnected, i.e., it is both stable (or independent) set and a cutset (or separator). Unlike general…

Data Structures and Algorithms · Computer Science 2024-07-03 Stefan Kratsch , Van Bang Le

We study the algorithmic properties of the graph class Chordal-ke, that is, graphs that can be turned into a chordal graph by adding at most k edges or, equivalently, the class of graphs of fill-in at most k. We discover that a number of…

Data Structures and Algorithms · Computer Science 2020-06-23 Fedor V. Fomin , Petr A. Golovach

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

Parameterized complexity allows us to analyze the time complexity of problems with respect to a natural parameter depending on the problem. Reoptimization looks for solutions or approximations for problem instances when given solutions to…

Computational Complexity · Computer Science 2019-07-31 Hans-Joachim Böckenhauer , Elisabet Burjons , Martin Raszyk , Peter Rossmanith

Tracking of moving objects is crucial to security systems and networks. Given a graph $G$, terminal vertices $s$ and $t$, and an integer $k$, the \textsc{Tracking Paths} problem asks whether there exists at most $k$ vertices, which if…

Data Structures and Algorithms · Computer Science 2020-08-24 Pratibha Choudhary , Venkatesh Raman