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We revisit the range $\tau$-majority problem, which asks us to preprocess an array $A[1..n]$ for a fixed value of $\tau \in (0,1/2]$, such that for any query range $[i,j]$ we can return a position in $A$ of each distinct $\tau$-majority…

Data Structures and Algorithms · Computer Science 2017-04-21 Pawel Gawrychowski , Patrick K. Nicholson

Let $P$ be a set of $m$ points in ${\mathbb R}^2$, let $\Sigma$ be a set of $n$ semi-algebraic sets of constant complexity in ${\mathbb R}^2$, let $(S,+)$ be a semigroup, and let $w: P \rightarrow S$ be a weight function on the points of…

Computational Geometry · Computer Science 2024-09-17 Pankaj K. Agarwal , Esther Ezra , Micha Sharir

We study the complexity of geometric problems on spaces of low fractal dimension. It was recently shown by [Sidiropoulos & Sridhar, SoCG 2017] that several problems admit improved solutions when the input is a pointset in Euclidean space…

Computational Complexity · Computer Science 2017-12-14 Anastasios Sidiropoulos , Kritika Singhal , Vijay Sridhar

We study the problem of PAC learning halfspaces with Massart noise. Given labeled samples $(x, y)$ from a distribution $D$ on $\mathbb{R}^{d} \times \{ \pm 1\}$ such that the marginal $D_x$ on the examples is arbitrary and the label $y$ of…

Machine Learning · Computer Science 2021-11-09 Ilias Diakonikolas , Daniel M. Kane

Several biological problems require the identification of regions in a sequence where some feature occurs within a target density range: examples including the location of GC-rich regions, identification of CpG islands, and sequence…

Data Structures and Algorithms · Computer Science 2013-08-15 Benjamin A. Burton , Mathias Hiron

Let $V$ be any vector space of multivariate degree-$d$ homogeneous polynomials with co-dimension at most $k$, and $S$ be the set of points where all polynomials in $V$ {\em nearly} vanish. We establish a qualitatively optimal upper bound on…

Machine Learning · Computer Science 2020-12-15 Ilias Diakonikolas , Daniel M. Kane

We consider the problem of summarizing a multi set of elements in $\{1, 2, \ldots , n\}$ under the constraint that no element appears more than $\ell$ times. The goal is then to answer \emph{rank} queries --- given $i\in\{1, 2, \ldots ,…

Data Structures and Algorithms · Computer Science 2017-04-26 Ran Ben Basat

Consider a pair of plane straight-line graphs, whose edges are colored red and blue, respectively, and let n be the total complexity of both graphs. We present a O(n log n)-time O(n)-space technique to preprocess such pair of graphs, that…

Computational Geometry · Computer Science 2017-05-09 John Iacono , Elena Khramtcova , Stefan Langerman

Given two strings $S$ and $P$, the Episode Matching problem is to find the shortest substring of $S$ that contains $P$ as a subsequence. The best known upper bound for this problem is $\tilde O(nm)$ by Das et al. (1997) , where $n,m$ are…

Data Structures and Algorithms · Computer Science 2024-02-15 Philip Bille , Inge Li Gørtz , Shay Mozes , Teresa Anna Steiner , Oren Weimann

We present a number of new results about range searching for colored (or "categorical") data: 1. For a set of $n$ colored points in three dimensions, we describe randomized data structures with $O(n\mathop{\rm polylog}n)$ space that can…

Data Structures and Algorithms · Computer Science 2020-03-27 Timothy M. Chan , Qizheng He , Yakov Nekrich

Allen's interval algebra is one of the most well-known calculi in qualitative temporal reasoning with numerous applications in artificial intelligence. Recently, there has been a surge of improvements in the fine-grained complexity of…

Computational Complexity · Computer Science 2023-05-26 Leif Eriksson , Victor Lagerkvist

We study the fundamental problem of clustering $n$ points into $K$ groups drawn from a mixture of isotropic Gaussians in $\mathbb{R}^d$. Specifically, we investigate the requisite minimal distance $\Delta$ between mean vectors to partially…

Statistics Theory · Mathematics 2026-02-27 Alexandra Carpentier , Nicolas Verzelen

Many uncertainty sets encountered in control systems analysis and design can be expressed in terms of semialgebraic sets, that is as the intersection of sets described by means of polynomial inequalities. Important examples are for instance…

Optimization and Control · Mathematics 2015-09-15 Fabrizio Dabbene , Didier Henrion , Constantino Lagoa

The k-means algorithm is a well-known method for partitioning n points that lie in the d-dimensional space into k clusters. Its main features are simplicity and speed in practice. Theoretically, however, the best known upper bound on its…

Computational Geometry · Computer Science 2008-12-03 Andrea Vattani

Given a set $P$ of $n$ uncertain points on the real line, each represented by its one-dimensional probability density function, we consider the problem of building data structures on $P$ to answer range queries of the following three types…

Computational Geometry · Computer Science 2015-01-13 Jian Li , Haitao Wang

In the Sparse Linear Regression (SLR) problem, given a $d \times n$ matrix $M$ and a $d$-dimensional query $q$, the goal is to compute a $k$-sparse $n$-dimensional vector $\tau$ such that the error $||M \tau-q||$ is minimized. This problem…

Computational Geometry · Computer Science 2018-05-01 Sariel Har-Peled , Piotr Indyk , Sepideh Mahabadi

Can Grover's algorithm speed up search of a physical region - for example a 2-D grid of size sqrt(n) by sqrt(n)? The problem is that sqrt(n) time seems to be needed for each query, just to move amplitude across the grid. Here we show that…

Quantum Physics · Physics 2007-05-23 Scott Aaronson , Andris Ambainis

We consider the problem of reporting convex hull points in an orthogonal range query in two dimensions. Formally, let $P$ be a set of $n$ points in $\mathbb{R}^{2}$. A point lies on the convex hull of a point set $S$ if it lies on the…

Computational Geometry · Computer Science 2013-07-24 Jatin Agarwal , Nadeem Moidu , Kishore Kothapalli , Kannan Srinathan

We study the sublinear multivariate mean estimation problem in $d$-dimensional Euclidean space. Specifically, we aim to find the mean $\mu$ of a ground point set $A$, which minimizes the sum of squared Euclidean distances of the points in…

Data Structures and Algorithms · Computer Science 2025-10-07 Beatrice Bertolotti , Matteo Russo , Chris Schwiegelshohn , Sudarshan Shyam

Given a set of n disjoint balls b1, . . ., bn in IRd, we provide a data structure, of near linear size, that can answer (1 \pm \epsilon)-approximate kth-nearest neighbor queries in O(log n + 1/\epsilon^d) time, where k and \epsilon are…

Computational Geometry · Computer Science 2014-10-30 Sariel Har-Peled , Nirman Kumar
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