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We consider the problem of identifying, from its first $m$ noisy moments, a probability distribution on $[0,1]$ of support $k<\infty$. This is equivalent to the problem of learning a distribution on $m$ observable binary random variables…

Machine Learning · Computer Science 2020-09-08 Spencer Gordon , Bijan Mazaheri , Leonard J. Schulman , Yuval Rabani

We consider a facility location problem, where the objective is to ``disperse'' a number of facilities, i.e., select a given number k of locations from a discrete set of n candidates, such that the average distance between selected…

Data Structures and Algorithms · Computer Science 2007-05-23 Sandor P. Fekete , Henk Meijer

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

The $k$-mismatch problem consists in computing the Hamming distance between a pattern $P$ of length $m$ and every length-$m$ substring of a text $T$ of length $n$, if this distance is no more than $k$. In many real-world applications, any…

The metric $k$-median problem is a textbook clustering problem. As input, we are given a metric space $V$ of size $n$ and an integer $k$, and our task is to find a subset $S \subseteq V$ of at most $k$ `centers' that minimizes the total…

Data Structures and Algorithms · Computer Science 2026-03-31 Martín Costa , Ermiya Farokhnejad

Consider a set $P$ of $n$ points picked uniformly and independently from $[0,1]^d$ for a constant dimension $d$ -- such a point set is extremely well behaved in many aspects. For example, for a fixed $r \in [0,1]$, we prove a new…

Computational Geometry · Computer Science 2023-11-01 Sariel Har-Peled , Elfarouk Harb

We study the k nearest neighbors problem in the plane for general, convex, pairwise disjoint sites of constant description complexity such as line segments, disks, and quadrilaterals and with respect to a general family of distance…

Computational Geometry · Computer Science 2019-10-29 Chih-Hung Liu

We present a new $4$-approximation algorithm for the Combinatorial Motion Planning problem which runs in $\mathcal{O}(n^2\alpha(n^2,n))$ time, where $\alpha$ is the functional inverse of the Ackermann function, and a fully distributed…

Discrete Mathematics · Computer Science 2018-05-24 Simran Dokania , Aditya Paliwal , Shrisha Rao

We present a polynomial time algorithm, which solves a nonstandard Variation of the well-known PARTITION-problem: Given positive integers $n, k$ and $t$ such that $t \geq n$ and $k \cdot t = {n+1 \choose 2}$, the algorithm partitions the…

Combinatorics · Mathematics 2023-06-22 Alexander Büchel , Ulrich Gilleßen , Kurt-Ulrich Witt

$k$-center is one of the most popular clustering models. While it admits a simple 2-approximation in polynomial time in general metrics, the Euclidean version is NP-hard to approximate within a factor of 1.93, even in the plane, if one…

Data Structures and Algorithms · Computer Science 2021-12-21 Sayan Bandyapadhyay , Zachary Friggstad , Ramin Mousavi

Given a set $ P $ of $n$ points and a set $ H $ of $n$ half-planes in the plane, we consider the problem of computing a smallest subset of points such that each half-plane contains at least one point of the subset. The previously best…

Computational Geometry · Computer Science 2025-01-07 Gang Liu , Haitao Wang

We propose a new finding $k$-minima algorithm and prove that its query complexity is $\mathcal{O}(\sqrt{kN})$, where $N$ is the number of data indices. Though the complexity is equivalent to that of an existing method, the proposed is…

Quantum Physics · Physics 2019-07-09 Kohei Miyamoto , Masakazu Iwamura , Koichi Kise

We present a scalable algorithm for the individually fair ($p$, $k$)-clustering problem introduced by Jung et al. and Mahabadi et al. Given $n$ points $P$ in a metric space, let $\delta(x)$ for $x\in P$ be the radius of the smallest ball…

Data Structures and Algorithms · Computer Science 2024-02-14 MohammadHossein Bateni , Vincent Cohen-Addad , Alessandro Epasto , Silvio Lattanzi

In this paper, we propose a distributed algorithm for the minimum dominating set problem. For some especial networks, we prove theoretically that the achieved answer by our proposed algorithm is a constant approximation factor of the exact…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-01-05 Sharareh Alipour , Ehsan Futuhi , Shayan Karimi

Given a point set S and an unknown metric d on S, we study the problem of efficiently partitioning S into k clusters while querying few distances between the points. In our model we assume that we have access to one versus all queries that…

Machine Learning · Computer Science 2014-08-12 Konstantin Voevodski , Maria-Florina Balcan , Heiko Roglin , Shang-Hua Teng , Yu Xia

Given a graph $G = (V, E)$ and an integer $k$, we study $k$-Vertex Seperator (resp. $k$-Edge Separator), where the goal is to remove the minimum number of vertices (resp. edges) such that each connected component in the resulting graph has…

Data Structures and Algorithms · Computer Science 2016-07-19 Euiwoong Lee

Given a $k$-CNF formula and an integer $s$, we study algorithms that obtain $s$ solutions to the formula that are maximally dispersed. For $s=2$, the problem of computing the diameter of a $k$-CNF formula was initiated by Creszenzi and…

Computational Complexity · Computer Science 2025-06-04 Per Austrin , Ioana O. Bercea , Mayank Goswami , Nutan Limaye , Adarsh Srinivasan

Given a set $P$ of $n$ points and a set $S$ of $n$ weighted disks in the plane, the disk coverage problem is to compute a subset of disks of smallest total weight such that the union of the disks in the subset covers all points of $P$. The…

Computational Geometry · Computer Science 2024-07-02 Gang Liu , Haitao Wang

We provide the first streaming algorithm for computing a provable approximation to the $k$-means of sparse Big data. Here, sparse Big Data is a set of $n$ vectors in $\mathbb{R}^d$, where each vector has $O(1)$ non-zeroes entries, and…

Data Structures and Algorithms · Computer Science 2016-02-09 Artem Barger , Dan Feldman

We study the $k$-center problem in the context of individual fairness. Let $P$ be a set of $n$ points in a metric space and $r_x$ be the distance between $x \in P$ and its $\lceil n/k \rceil$-th nearest neighbor. The problem asks to…

Data Structures and Algorithms · Computer Science 2025-03-26 Matthijs Ebbens , Nicole Funk , Jan Höckendorff , Christian Sohler , Vera Weil