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We study the approximate range searching for three variants of the clustering problem with a set $P$ of $n$ points in $d$-dimensional Euclidean space and axis-parallel rectangular range queries: the $k$-median, $k$-means, and $k$-center…

Computational Geometry · Computer Science 2018-03-13 Eunjin Oh , Hee-Kap Ahn

In the Random Subset Sum Problem, given $n$ i.i.d. random variables $X_1, ..., X_n$, we wish to approximate any point $z \in [-1,1]$ as the sum of a suitable subset $X_{i_1(z)}, ..., X_{i_s(z)}$ of them, up to error $\varepsilon$. Despite…

Neural and Evolutionary Computing · Computer Science 2022-11-18 Luca Becchetti , Arthur Carvalho Walraven da Cunha , Andrea Clementi , Francesco d'Amore , Hicham Lesfari , Emanuele Natale , Luca Trevisan

In this paper, we give a faster width-dependent algorithm for mixed packing-covering LPs. Mixed packing-covering LPs are fundamental to combinatorial optimization in computer science and operations research. Our algorithm finds a $1+\eps$…

Optimization and Control · Mathematics 2019-10-15 Digvijay Boob , Saurabh Sawlani , Di Wang

The input to the NP-hard Point Line Cover problem (PLC) consists of a set $P$ of $n$ points on the plane and a positive integer $k$, and the question is whether there exists a set of at most $k$ lines which pass through all points in $P$. A…

Data Structures and Algorithms · Computer Science 2013-07-10 Stefan Kratsch , Geevarghese Philip , Saurabh Ray

We study the problem of Covering Orthogonal Polygons with Rectangles. For polynomial-time algorithms, the best-known approximation factor is $O(\sqrt{\log n})$ when the input polygon may have holes [Kumar and Ramesh, STOC '99, SICOMP '03],…

Computational Geometry · Computer Science 2024-06-25 Aniket Basu Roy

Range-aggregate query is an important type of queries with numerous applications. It aims to obtain some structural information (defined by an aggregate function $F(\cdot)$) of the points (from a point set $P$) inside a given query range…

Computational Geometry · Computer Science 2022-06-16 Ziyun Huang , Jinhui Xu

We consider the task of fitting low-dimensional embeddings to high-dimensional data. In particular, we study the $k$-Euclidean Metric Violation problem ($\textsf{$k$-EMV}$), where the input is $D \in \mathbb{R}^{\binom{n}{2}}_{\geq 0}$ and…

Data Structures and Algorithms · Computer Science 2025-09-12 Prashanti Anderson , Ainesh Bakshi , Samuel B. Hopkins

We use entropy numbers in combination with the polynomial method to derive a new general lower bound for the n-th minimal error in the quantum setting of information-based complexity. As an application, we improve some lower bounds on…

Quantum Physics · Physics 2007-05-23 Stefan Heinrich

One of the oldest problems in the data stream model is to approximate the $p$-th moment $\|\mathcal{X}\|_p^p = \sum_{i=1}^n |\mathcal{X}_i|^p$ of an underlying vector $\mathcal{X} \in \mathbb{R}^n$, which is presented as a sequence of…

Data Structures and Algorithms · Computer Science 2019-07-15 Rajesh Jayaram , David P. Woodruff

In the problem of semialgebraic range searching, we are to preprocess a set of points in $\mathbb{R}^D$ such that the subset of points inside a semialgebraic region described by $O(1)$ polynomial inequalities of degree $\Delta$ can be found…

Computational Geometry · Computer Science 2022-03-16 Peyman Afshani , Pingan Cheng

This paper studies the \emph{$\varepsilon$-approximate range emptiness} problem, where the task is to represent a set $S$ of $n$ points from $\{0,\ldots,U-1\}$ and answer emptiness queries of the form "$[a ; b]\cap S \neq \emptyset$ ?" with…

Data Structures and Algorithms · Computer Science 2014-07-11 Mayank Goswami , Allan Grønlund , Kasper Green Larsen , Rasmus Pagh

We consider the problem of encoding range minimum queries (RMQs): given an array A[1..n] of distinct totally ordered values, to pre-process A and create a data structure that can answer the query RMQ(i,j), which returns the index containing…

Data Structures and Algorithms · Computer Science 2013-11-19 Pooya Davoodi , Gonzalo Navarro , Rajeev Raman , S. Srinivasa Rao

The nearest neighbor problem is defined as follows: Given a set $P$ of $n$ points in some metric space $(X,D)$, build a data structure that, given any point $q$, returns a point in $P$ that is closest to $q$ (its "nearest neighbor" in $P$).…

Data Structures and Algorithms · Computer Science 2018-06-27 Alexandr Andoni , Piotr Indyk , Ilya Razenshteyn

We consider the problem of estimating a $d$-dimensional discrete distribution from its samples observed under a $b$-bit communication constraint. In contrast to most previous results that largely focus on the global minimax error, we study…

Information Theory · Computer Science 2021-11-02 Wei-Ning Chen , Peter Kairouz , Ayfer Özgür

We consider the differentially private (DP) facility location problem in the so called super-set output setting proposed by Gupta et al. [SODA 2010]. The current best known expected approximation ratio for an $\epsilon$-DP algorithm is…

Data Structures and Algorithms · Computer Science 2024-03-11 Pasin Manurangsi

In this paper we investigate the problem of building a static data structure that represents a string s using space close to its compressed size, and allows fast access to individual characters of s. This type of structures was investigated…

Computational Complexity · Computer Science 2012-05-04 Shiteng Chen , Elad Verbin , Wei Yu

We consider a general model for representing and manipulating parametric curves, in which a curve is specified by a black box mapping a parameter value between 0 and 1 to a point in Euclidean d-space. In this model, we consider the…

Computational Geometry · Computer Science 2007-05-23 Ilya Baran , Erik D. Demaine

In this paper, we present a low-diameter decomposition algorithm in the LOCAL model of distributed computing that succeeds with probability $1 - 1/poly(n)$. Specifically, we show how to compute an $\left(\epsilon, O\left(\frac{\log…

Data Structures and Algorithms · Computer Science 2023-07-25 Yi-Jun Chang , Zeyong Li

Evaluating the statistical dimension is a common tool to determine the asymptotic phase transition in compressed sensing problems with Gaussian ensemble. Unfortunately, the exact evaluation of the statistical dimension is very difficult and…

Information Theory · Computer Science 2019-06-06 Sajad Daei , Farzan Haddadi , Arash Amini , Martin Lotz

In this paper we study the four-dimensional dominance range reporting problem and present data structures with linear or almost-linear space usage. Our results can be also used to answer four-dimensional queries that are bounded on five…

Data Structures and Algorithms · Computer Science 2020-03-17 Yakov Nekrich