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We give the first polynomial-time approximation schemes (PTASs) for the following problems: (1) uniform facility location in edge-weighted planar graphs; (2) $k$-median and $k$-means in edge-weighted planar graphs; (3) $k$-means in…

Data Structures and Algorithms · Computer Science 2016-04-08 Vincent Cohen-Addad , Philip N. Klein , Claire Mathieu

For a graph $G$ on $n$ vertices, naively sampling the position of a random walk of at time $t$ requires work $\Omega(t)$. We desire local access algorithms supporting $\text{position}(G,s,t)$ queries, which return the position of a random…

Data Structures and Algorithms · Computer Science 2021-02-16 Amartya Shankha Biswas , Edward Pyne , Ronitt Rubinfeld

We study the algorithmic problem of sparse mean estimation in the presence of adversarial outliers. Specifically, the algorithm observes a \emph{corrupted} set of samples from $\mathcal{N}(\mu,\mathbf{I}_d)$, where the unknown mean $\mu \in…

Data Structures and Algorithms · Computer Science 2024-03-08 Ankit Pensia

We show that Reed-Solomon codes of dimension $k$ and block length $n$ over any finite field $\mathbb{F}$ can be deterministically list decoded from agreement $\sqrt{(k-1)n}$ in time $\text{poly}(n, \log |\mathbb{F}|)$. Prior to this work,…

Computational Complexity · Computer Science 2026-03-26 Soham Chatterjee , Prahladh Harsha , Mrinal Kumar

We consider the Low Rank Approximation problem, where the input consists of a matrix $A \in \mathbb{R}^{n_R \times n_C}$ and an integer $k$, and the goal is to find a matrix $B$ of rank at most $k$ that minimizes $\| A - B \|_0$, which is…

Data Structures and Algorithms · Computer Science 2023-11-03 Vincent Cohen-Addad , Chenglin Fan , Suprovat Ghoshal , Euiwoong Lee , Arnaud de Mesmay , Alantha Newman , Tony Chang Wang

Suppose a language $L$ can be decided by a bounded-error randomized algorithm that runs in space $S$ and time $n \cdot \text{poly}(S)$. We give a randomized algorithm for $L$ that still runs in space $O(S)$ and time $n \cdot \text{poly}(S)$…

Computational Complexity · Computer Science 2019-05-17 William M. Hoza

Robust mean estimation is one of the most important problems in statistics: given a set of samples in $\mathbb{R}^d$ where an $\alpha$ fraction are drawn from some distribution $D$ and the rest are adversarially corrupted, we aim to…

Machine Learning · Computer Science 2022-12-07 Shiwei Zeng , Jie Shen

Given a quadratic map Q : K^n -> K^k defined over a computable subring D of a real closed field K, and a polynomial p(Y_1,...,Y_k) of degree d, we consider the zero set Z=Z(p(Q(X)),K^n) of the polynomial p(Q(X_1,...,X_n)). We present a…

Symbolic Computation · Computer Science 2007-05-23 Dima Grigoriev , Dmitrii V. Pasechnik

A decentralized search algorithm is a method of routing on a random graph that uses only limited, local, information about the realization of the graph. In some random graph models it is possible to define such algorithms which produce…

Probability · Mathematics 2008-04-04 Oskar Sandberg

We propose a way to transform synchronous distributed algorithms solving locally greedy and mendable problems into self-stabilizing algorithms in anonymous networks. Mendable problems are a generalization of greedy problems where any…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-04-20 Johanne Cohen , Laurence Pilard , Mikaël Rabie , Jonas Sénizergues

Local search is a widely-employed strategy for finding good solutions to Traveling Salesman Problem. We analyze the problem of determining whether the weight of a given cycle can be decreased by a popular $k$-opt move. Earlier work has…

Data Structures and Algorithms · Computer Science 2019-09-04 Édouard Bonnet , Yoichi Iwata , Bart M. P. Jansen , Łukasz Kowalik

The quantum k-Local Hamiltonian problem is a natural generalization of classical constraint satisfaction problems (k-CSP) and is complete for QMA, a quantum analog of NP. Although the complexity of k-Local Hamiltonian problems has been well…

Quantum Physics · Physics 2021-11-16 Ojas Parekh , Kevin Thompson

We present a Monte Carlo algorithm for Hamiltonicity detection in an $n$-vertex undirected graph running in $O^*(1.657^{n})$ time. To the best of our knowledge, this is the first superpolynomial improvement on the worst case runtime for the…

Data Structures and Algorithms · Computer Science 2010-08-04 Andreas Björklund

We revisit a fundamental problem in string matching: given a pattern of length m and a text of length n, both over an alphabet of size $\sigma$, compute the Hamming distance between the pattern and the text at every location. Several…

Data Structures and Algorithms · Computer Science 2020-01-03 Timothy M. Chan , Shay Golan , Tomasz Kociumaka , Tsvi Kopelowitz , Ely Porat

A locating-dominating set $D$ of a graph $G$ is a dominating set of $G$ where each vertex not in $D$ has a unique neighborhood in $D$, and the Locating-Dominating Set problem asks if $G$ contains such a dominating set of bounded size. This…

Data Structures and Algorithms · Computer Science 2023-10-10 Márcia R. Cappelle , Guilherme C. M. Gomes , Vinicius F. dos Santos

We unveil an alluring alternative to parametric search that applies to both the non-geodesic and geodesic Fr\'echet optimization problems. This randomized approach is based on a variant of red-blue intersections and is appealing due to its…

Data Structures and Algorithms · Computer Science 2008-05-21 Atlas F. Cook , Carola Wenk

The Makespan Scheduling problem is an extensively studied NP-hard problem, and its simplest version looks for an allocation approach for a set of jobs with deterministic processing times to two identical machines such that the makespan is…

Neural and Evolutionary Computing · Computer Science 2025-04-25 Feng Shi , Daoyu Huang , Xiankun Yan , Frank Neumann

Diameter -- the task of computing the length of a longest shortest path -- is a fundamental graph problem. Assuming the Strong Exponential Time Hypothesis, there is no $O(n^{1.99})$-time algorithm even in sparse graphs [Roditty and…

Data Structures and Algorithms · Computer Science 2020-12-22 Matthias Bentert , André Nichterlein

We develop a new method to efficiently sample synthetic networks that preserve the d-hop neighborhood structure of a given network for any given d. The proposed algorithm trades off the diversity in network samples against the depth of the…

Social and Information Networks · Computer Science 2023-09-21 Felix I. Stamm , Michael Scholkemper , Markus Strohmaier , Michael T. Schaub

Given n elements with nonnegative integer weights w1,..., wn and an integer capacity C, we consider the counting version of the classic knapsack problem: find the number of distinct subsets whose weights add up to at most the given…

Data Structures and Algorithms · Computer Science 2010-08-11 Daniel Stefankovic , Santosh Vempala , Eric Vigoda