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Given a matrix $A \in \mathbb{R}^{n\times n}$, we consider the problem of maximizing $x^TAx$ subject to the constraint $x \in \{-1,1\}^n$. This problem, called MaxQP by Charikar and Wirth [FOCS'04], generalizes MaxCut and has natural…

Data Structures and Algorithms · Computer Science 2020-12-16 Danny Hermelin , Leon Kellerhals , Rolf Niedermeier , Rami Pugatch

We give a 2-approximation algorithm for Non-Uniform Sparsest Cut that runs in time $n^{O(k)}$, where $k$ is the treewidth of the graph. This improves on the previous $2^{2^k}$-approximation in time $\poly(n) 2^{O(k)}$ due to Chlamt\'a\v{c}…

Data Structures and Algorithms · Computer Science 2013-05-08 Anupam Gupta , Kunal Talwar , David Witmer

There has been considerable recent interest in distribution-tests whose run-time and sample requirements are sublinear in the domain-size $k$. We study two of the most important tests under the conditional-sampling model where each query…

Data Structures and Algorithms · Computer Science 2015-04-17 Moein Falahatgar , Ashkan Jafarpour , Alon Orlitsky , Venkatadheeraj Pichapathi , Ananda Theertha Suresh

We give a number of approximation metatheorems for monotone maximization problems expressible in the first-order logic, in substantially more general settings than the previously known. We obtain * constant-factor approximation algorithm in…

Discrete Mathematics · Computer Science 2021-10-12 Zdeněk Dvořák

K\"onig's theorem states that on bipartite graphs the size of a maximum matching equals the size of a minimum vertex cover. It is known from prior work that for every \epsilon > 0 there exists a constant-time distributed algorithm that…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-12-24 Mika Göös , Jukka Suomela

Geometric data structures have been extensively studied in the regime where the dimension is much smaller than the number of input points. But in many scenarios in Machine Learning, the dimension can be much higher than the number of points…

Data Structures and Algorithms · Computer Science 2025-04-07 Martin G. Herold , Danupon Nanongkai , Joachim Spoerhase , Nithin Varma , Zihang Wu

We study spectral approaches for the MAX-2-LIN(k) problem, in which we are given a system of $m$ linear equations of the form $x_i - x_j \equiv c_{ij}\mod k$, and required to find an assignment to the $n$ variables $\{x_i\}$ that maximises…

Data Structures and Algorithms · Computer Science 2018-11-28 Huan Li , He Sun , Luca Zanetti

We investigate the relation between $\delta$ and $\epsilon$ required for obtaining a $(1+\delta)$-approximation in time $N^{2-\epsilon}$ for closest pair problems under various distance metrics, and for other related problems in…

Data Structures and Algorithms · Computer Science 2023-11-03 Elie Abboud , Noga Ron-Zewi

Any graph with maximum degree $\Delta$ admits a proper vertex coloring with $\Delta + 1$ colors that can be found via a simple sequential greedy algorithm in linear time and space. But can one find such a coloring via a sublinear algorithm?…

Data Structures and Algorithms · Computer Science 2019-01-08 Sepehr Assadi , Yu Chen , Sanjeev Khanna

In this work, we study the classic submodular maximization problem under knapsack constraints and beyond. We first present an $(7/16-\varepsilon)$-approximate algorithm for single knapsack constraint, which requires…

Data Structures and Algorithms · Computer Science 2020-12-22 Wenxin Li

In this paper we present linear time approximation schemes for several generalized matching problems on nonbipartite graphs. Our results include $O_\epsilon(m)$-time algorithms for $(1-\epsilon)$-maximum weight $f$-factor and…

Data Structures and Algorithms · Computer Science 2020-05-11 Dawei Huang , Seth Pettie

We consider the problems ZERO EXTENSION and METRIC LABELLING under the paradigm of parameterized complexity. These are natural, well-studied problems with important applications, but have previously not received much attention from…

Data Structures and Algorithms · Computer Science 2018-02-19 Felix Reidl , Magnus Wahlström

Length-constrained expander decompositions are a new graph decomposition that has led to several recent breakthroughs in fast graph algorithms. Roughly, an $(h, s)$-length $\phi$-expander decomposition is a small collection of length…

Data Structures and Algorithms · Computer Science 2025-10-14 Greg Bodwin , Bernhard Haeupler , D Ellis Hershkowitz , Zihan Tan

The area of sublinear algorithms have recently received a lot of attention. In this setting, one has to choose specific access model for the input, as the algorithm does not have time to pre-process or even to see the whole input. A…

Data Structures and Algorithms · Computer Science 2020-09-24 Jakub Tětek

We bound the smoothed running time of the FLIP algorithm for local Max-Cut as a function of $\alpha$, the arboricity of the input graph. We show that, with high probability and in expectation, the following holds (where $n$ is the number of…

Data Structures and Algorithms · Computer Science 2024-04-23 Gregory Schwartzman

We prove essentially tight lower bounds, conditionally to the Exponential Time Hypothesis, for two fundamental but seemingly very different cutting problems on surface-embedded graphs: the Shortest Cut Graph problem and the Multiway Cut…

Computational Complexity · Computer Science 2021-02-18 Vincent Cohen-Addad , Éric Colin de Verdière , Daniel Marx , Arnaud de Mesmay

Expander decompositions have become one of the central frameworks in the design of fast algorithms. For an undirected graph $G=(V,E)$, a near-optimal $\phi$-expander decomposition is a partition $V_1, V_2, \ldots, V_k$ of the vertex set $V$…

Data Structures and Algorithms · Computer Science 2025-01-07 Daoyuan Chen , Simon Meierhans , Maximilian Probst Gutenberg , Thatchaphol Saranurak

A $(\phi,\epsilon)$-expander-decomposition of a graph $G$ (with $n$ vertices and $m$ edges) is a partition of $V$ into clusters $V_1,\ldots,V_k$ with conductance $\Phi(G[V_i]) \ge \phi$, such that there are at most $\epsilon m$…

Data Structures and Algorithms · Computer Science 2025-02-04 Daniel Agassy , Dani Dorfman , Haim Kaplan

We provide a new approach for establishing hardness of approximation results, based on the theory recently introduced by the author. It allows one to directly show that approximating a problem beyond a certain threshold requires…

Computational Complexity · Computer Science 2024-02-23 Ali Çivril

Given a collection of $m$ sets from a universe $\mathcal{U}$, the Maximum Set Coverage problem consists of finding $k$ sets whose union has largest cardinality. This problem is NP-Hard, but the solution can be approximated by a polynomial…

Data Structures and Algorithms · Computer Science 2023-12-13 Stephen Jaud , Anthony Wirth , Farhana Choudhury
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