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The $k$-ExactCover problem is a parameterized version of the ExactCover problem, in which we are given a universe $U$, a collection $S$ of subsets of $U$, and an integer $k$, and the task is to determine whether $U$ can be partitioned into…

Computational Complexity · Computer Science 2019-05-21 Venkatesan Guruswami , Patrick Lin

We show that Set Cover on instances with $N$ elements cannot be approximated within $(1-\gamma)\ln N$-factor in time exp($N^{\gamma-\delta})$, for any $0 < \gamma < 1$ and any $\delta > 0$, assuming the Exponential Time Hypothesis. This…

Data Structures and Algorithms · Computer Science 2020-08-13 Marek Cygan , Magnús M. Halldórsson , Guy Kortsarz

We revisit the classic Maximum $k$-Coverage problem: Determine the largest number $t$ of elements that can be covered by choosing $k$ sets from a given family $\mathcal{F} = \{S_1,\dots, S_n\}$ of a size-$u$ universe. A notable special case…

Data Structures and Algorithms · Computer Science 2026-01-26 Nick Fischer , Marvin Künnemann , Mirza Redzic

Given a simple graph $G$ and an integer $k$, the goal of $k$-Clique problem is to decide if $G$ contains a complete subgraph of size $k$. We say an algorithm approximates $k$-Clique within a factor $g(k)$ if it can find a clique of size at…

Computational Complexity · Computer Science 2022-08-04 Bingkai Lin , Xuandi Ren , Yican Sun , Xiuhan Wang

In the classic maximum coverage problem, we are given subsets $T_1, \dots, T_m$ of a universe $[n]$ along with an integer $k$ and the objective is to find a subset $S \subseteq [m]$ of size $k$ that maximizes $C(S) := |\cup_{i \in S} T_i|$.…

Data Structures and Algorithms · Computer Science 2022-05-24 Siddharth Barman , Omar Fawzi , Suprovat Ghoshal , Emirhan Gürpınar

An upper dominating set is a minimal dominating set in a graph. In the \textsc{Upper Dominating Set} problem, the goal is to find an upper dominating set of maximum size. We study the complexity of parameterized algorithms for \textsc{Upper…

Data Structures and Algorithms · Computer Science 2021-01-20 Louis Dublois , Michael Lampis , Vangelis Th. Paschos

We study the complexity of the maximum coverage problem, restricted to set systems of bounded VC-dimension. Our main result is a fixed-parameter tractable approximation scheme: an algorithm that outputs a $(1-\eps)$-approximation to the…

Computational Geometry · Computer Science 2011-12-06 Ashwinkumar Badanidiyuru , Robert Kleinberg , Hooyeon Lee

The $k$-means problem is a classic objective for modeling clustering in a metric space. Given a set of points in a metric space, the goal is to find $k$ representative points so as to minimize the sum of the squared distances from each…

Computational Geometry · Computer Science 2026-03-31 Vincent Cohen-Addad , Karthik C. S. , David Saulpic , Chris Schwiegelshohn

A long-standing open question is which graph class is the most general one permitting constant-time constant-factor approximations for dominating sets. The approximation ratio has been bounded by increasingly general parameters such as…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-08-26 Christoph Lenzen , Sophie Wenning

In this paper we focus on problems which do not admit a constant-factor approximation in polynomial time and explore how quickly their approximability improves as the allowed running time is gradually increased from polynomial to…

Data Structures and Algorithms · Computer Science 2015-02-23 Édouard Bonnet , Michael Lampis , Vangelis Th. Paschos

Search patterns of randomly oriented steps of different lengths have been observed on all scales of the biological world, ranging from the microscopic to the ecological, including in protein motors, bacteria, T-cells, honeybees, marine…

Quantitative Methods · Quantitative Biology 2020-02-14 Brieuc Guinard , Amos Korman

We examine the possibility of approximating Maximum Vertex-Disjoint Shortest Paths. In this problem, the input is an edge-weighted (directed or undirected) $n$-vertex graph $G$ along with $k$ terminal pairs…

Data Structures and Algorithms · Computer Science 2025-04-23 Matthias Bentert , Fedor V. Fomin , Petr A. Golovach

We present a series of almost settled inapproximability results for three fundamental problems. The first in our series is the subexponential-time inapproximability of the maximum independent set problem, a question studied in the area of…

Computational Complexity · Computer Science 2013-08-20 Parinya Chalermsook , Bundit Laekhanukit , Danupon Nanongkai

Following recent advances in combining approximation algorithms with fixed-parameter tractability (FPT), we study FPT-time approximation algorithms for minimum-norm $k$-clustering problems, parameterized by the number $k$ of open…

Data Structures and Algorithms · Computer Science 2026-05-07 Han Dai , Shi Li , Sijin Peng

We present a simple deterministic reduction which, assuming the Exponential Time Hypothesis ($\mathsf{ETH}$), yields tight lower bounds for approximating the parameterized Maximum Likelihood Decoding problem ($\mathsf{MLD}$) and the…

Computational Complexity · Computer Science 2026-05-12 Rishav Gupta , Bingkai Lin , Xin Zheng

Given an $n$-vertex bipartite graph $I=(S,U,E)$, the goal of set cover problem is to find a minimum sized subset of $S$ such that every vertex in $U$ is adjacent to some vertex of this subset. It is NP-hard to approximate set cover to…

Computational Complexity · Computer Science 2019-04-29 Bingkai Lin

In the Densest $k$-Subgraph problem, given an undirected graph $G$ and an integer $k$, the goal is to find a subgraph of $G$ on $k$ vertices that contains maximum number of edges. Even though the state-of-the-art algorithm for the problem…

Computational Complexity · Computer Science 2017-04-11 Pasin Manurangsi

We show that there is no $2^{o(k^2)} n^{O(1)}$ time algorithm for Independent Set on $n$-vertex graphs with rank-width $k$, unless the Exponential Time Hypothesis (ETH) fails. Our lower bound matches the $2^{O(k^2)} n^{O(1)}$ time algorithm…

Data Structures and Algorithms · Computer Science 2022-12-09 Benjamin Bergougnoux , Tuukka Korhonen , Jesper Nederlof

Given a line segment $I=[0,L]$, the so-called barrier, and a set of $n$ sensors with varying ranges positioned on the line containing $I$, the barrier coverage problem is to move the sensors so that they cover $I$, while minimising the…

Data Structures and Algorithms · Computer Science 2017-10-02 Serge Gaspers , Joachim Gudmundsson , Julián Mestre , Stefan Rümmele

The subspace approximation problem Subspace($k$,$p$) asks for a $k$-dimensional linear subspace that fits a given set of points optimally, where the error for fitting is a generalization of the least squares fit and uses the $\ell_{p}$ norm…

Data Structures and Algorithms · Computer Science 2011-01-04 Amit Deshpande , Kasturi Varadarajan , Madhur Tulsiani , Nisheeth K. Vishnoi
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