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We give an explicit (in particular, deterministic polynomial time) construction of subspaces X of R^N of dimension (1-o(1))N such that for every element x in X, |x|_1 and N^{1/2} |x|_2 are equivalent up to a factor of (log N)^{log log log…

Metric Geometry · Mathematics 2009-03-26 Venkatesan Guruswami , James R. Lee , Alexander Razborov

Thorup [FOCS'01, JACM'04] and Klein [SODA'01] independently showed that there exists a $(1+\epsilon)$-approximate distance oracle for planar graphs with $O(n (\log n)\epsilon^{-1})$ space and $O(\epsilon^{-1})$ query time. While the…

Data Structures and Algorithms · Computer Science 2022-07-13 Hung Le

The construction of $r$-nets offers a powerful tool in computational and metric geometry. We focus on high-dimensional spaces and present a new randomized algorithm which efficiently computes approximate $r$-nets with respect to Euclidean…

Computational Geometry · Computer Science 2017-05-09 Georgia Avarikioti , Ioannis Z. Emiris , Loukas Kavouras , Ioannis Psarros

We design a new distribution over $\poly(r \eps^{-1}) \times n$ matrices $S$ so that for any fixed $n \times d$ matrix $A$ of rank $r$, with probability at least 9/10, $\norm{SAx}_2 = (1 \pm \eps)\norm{Ax}_2$ simultaneously for all $x \in…

Data Structures and Algorithms · Computer Science 2013-04-08 Kenneth L. Clarkson , David P. Woodruff

This work suggests faster and space-efficient index construction algorithms for LSH for Euclidean distance (\textit{a.k.a.}~\ELSH) and cosine similarity (\textit{a.k.a.}~\SRP). The index construction step of these LSHs relies on grouping…

Data Structures and Algorithms · Computer Science 2025-07-18 Bhisham Dev Verma , Rameshwar Pratap

In the Euclidean TSP with neighborhoods (TSPN), we are given a collection of n regions (neighborhoods) and we seek a shortest tour that visits each region. As a generalization of the classical Euclidean TSP, TSPN is also NP-hard. In this…

Computational Geometry · Computer Science 2017-03-07 Adrian Dumitrescu , Joseph S. B. Mitchell

This paper presents a near-optimal distributed approximation algorithm for the minimum-weight connected dominating set (MCDS) problem. The presented algorithm finds an $O(\log n)$ approximation in $\tilde{O}(D+\sqrt{n})$ rounds, where $D$…

Data Structures and Algorithms · Computer Science 2014-05-01 Mohsen Ghaffari

For a metric space $(X, d)$, a family $\mathcal{H}$ of locality sensitive hash functions is called $(r, cr, p_1, p_2)$ sensitive if a randomly chosen function $h\in \mathcal{H}$ has probability at least $p_1$ (at most $p_2$) to map any $a,…

Computational Geometry · Computer Science 2026-03-23 Chengyuan Deng , Jie Gao , Kevin Lu , Feng Luo , Cheng Xin

We study data structures for storing a set of polygonal curves in ${\rm R}^d$ such that, given a query curve, we can efficiently retrieve similar curves from the set, where similarity is measured using the discrete Fr\'echet distance or the…

Computational Geometry · Computer Science 2017-03-14 Anne Driemel , Francesco Silvestri

In this paper, we study robust beamforming design for near-field physical-layer-security (PLS) systems, where a base station (BS) equipped with an extremely large-scale array (XL-array) serves multiple near-field legitimate users (Bobs) in…

Signal Processing · Electrical Eng. & Systems 2026-01-21 Chao Zhou , Changsheng You , Cong Zhou , Chengwen Xing , Jianhua Zhang

We consider the locality of encoding and decoding operations in distributed storage systems (DSS), and propose a new class of codes, called locally encodable and decodable codes (LEDC), that provides a higher degree of operational locality…

Information Theory · Computer Science 2015-04-21 Son Hoang Dau , Han Mao Kiah , Wentu Song , Chau Yuen

Computing the approximate quantiles or ranks of a stream is a fundamental task in data monitoring. Given a stream of elements $x_1, x_2, \dots, x_n$ and a query $x$, a relative-error quantile estimation algorithm can estimate the rank of…

Data Structures and Algorithms · Computer Science 2024-11-05 Elena Gribelyuk , Pachara Sawettamalya , Hongxun Wu , Huacheng Yu

We introduce a new class of objectives for optimal transport computations of datasets in high-dimensional Euclidean spaces. The new objectives are parametrized by $\rho \geq 1$, and provide a metric space $\mathcal{R}_{\rho}(\cdot, \cdot)$…

Data Structures and Algorithms · Computer Science 2023-07-20 Moses Charikar , Beidi Chen , Christopher Re , Erik Waingarten

Higher-order exceptional points (EPs) in optical structures enable ultra-sensitive responses to perturbations. However, previous investigations on higher-order EPs have predominantly focused on coupled systems, leaving their fundamental…

We consider the problem of building Distance Sensitivity Oracles (DSOs). Given a directed graph $G=(V, E)$ with edge weights in $\{1, 2, \dots, M\}$, we need to preprocess it into a data structure, and answer the following queries: given…

Data Structures and Algorithms · Computer Science 2021-09-03 Hanlin Ren

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

We show that in the limit of small Rossby number $\eps$, the primitive equations of the ocean (OPEs) can be approximated by ``higher-order quasi-geostrophic equations'' up to an exponential accuracy in $\eps$. This approximation assumes…

Analysis of PDEs · Mathematics 2007-05-23 R. Temam , D. Wirosoetisno

This paper is devoted to order-one explicit approximations of random periodic solutions to multiplicative noise driven stochastic differential equations (SDEs) with non-globally Lipschitz coefficients. The existence of the random periodic…

Probability · Mathematics 2025-01-06 Yujia Guo , Xiaojie Wang , Yue Wu

We present \textsf{ModularSubsetSelection} (MSS), a new algorithm for locally differentially private (LDP) frequency estimation. Given a universe of size $k$ and $n$ users, our $\varepsilon$-LDP mechanism encodes each input via a Residue…

Cryptography and Security · Computer Science 2025-11-18 Héber H. Arcolezi

We examine the rate of convergence of the Lasso estimator of lower dimensional components of the high-dimensional parameter. Under bounds on the $\ell_1$-norm on the worst possible sub-direction these rates are of order $\sqrt {|J| \log p /…

Statistics Theory · Mathematics 2014-03-28 Sara van de Geer