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We study the following range searching problem: Preprocess a set $P$ of $n$ points in the plane with respect to a set $\mathcal{O}$ of $k$ orientations % , for a constant, in the plane so that given an $\mathcal{O}$-oriented convex polygon…

Computational Geometry · Computer Science 2019-10-22 Eunjin Oh , Hee-Kap Ahn

A new algorithm for the determination of the relative convex hull in the plane of a simple polygon A with respect to another simple polygon B which contains A, is proposed. The relative convex hull is also known as geodesic convex hull, and…

Computational Geometry · Computer Science 2016-05-02 P. Wiederhold , H. Reyes

Given a convex polygon $P$ with $n$ vertices, the two-center problem is to find two congruent closed disks of minimum radius such that they completely cover $P$. We propose an algorithm for this problem in the streaming setup, where the…

Computational Geometry · Computer Science 2015-12-09 Sanjib Sadhu , Sasanka Roy , Soumen Nandi , Anil Maheswari , Subhas C. Nandy

In this paper, we study the fundamental open question of finding the optimal high-order algorithm for solving smooth convex minimization problems. Arjevani et al. (2019) established the lower bound $\Omega\left(\epsilon^{-2/(3p+1)}\right)$…

Optimization and Control · Mathematics 2022-05-20 Dmitry Kovalev , Alexander Gasnikov

A polynomial algorithm is obtained for the NP-complete linear ordering problem.

Computational Complexity · Computer Science 2007-05-23 Givi Bolotashvili

We devise a polynomial-time algorithm for partitioning a simple polygon $P$ into a minimum number of star-shaped polygons. The question of whether such an algorithm exists has been open for more than four decades [Avis and Toussaint,…

Computational Geometry · Computer Science 2026-03-11 Mikkel Abrahamsen , Joakim Blikstad , André Nusser , Hanwen Zhang

A given order type in the plane can be represented by a point set. However, it might be difficult to recognize the orientations of some point triples. Recently, Aichholzer \etal \cite{abh19} introduced exit graphs for visualizing order…

Computational Geometry · Computer Science 2020-12-01 Sergey Bereg , Mohammadreza Haghpanah

We envision programmable matter as a system of nano-scale agents (called particles) with very limited computational capabilities that move and compute collectively to achieve a desired goal. We use the geometric amoebot model as our…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-08-15 Joshua J. Daymude , Robert Gmyr , Kristian Hinnenthal , Irina Kostitsyna , Christian Scheideler , Andréa W. Richa

Let $P$ be a set of $n$ points in general position on the plane. A set of closed convex polygons with vertices in $P$, and with pairwise disjoint interiors is called a convex decomposition of $P$ if their union is the convex hull of $P$,…

Combinatorics · Mathematics 2019-09-16 Toshinori Sakai , Jorge Urrutia

Tverberg's theorem states that any set of $t(r,d)=(r-1)(d+1)+1$ points in $\mathbb{R}^d$ can be partitioned into $r$ subsets whose convex hulls have non-empty $r$-fold intersection. Moreover, generic collections of fewer points cannot be so…

Combinatorics · Mathematics 2023-11-10 Steven Simon , Tobias Timofeyev

Let $P$ be a set of $n$ points in the plane. We compute the value of $\theta\in [0,2\pi)$ for which the rectilinear convex hull of $P$, denoted by $\mathcal{RH}_\theta(P)$, has minimum (or maximum) area in optimal $O(n\log n)$ time and…

Computational Geometry · Computer Science 2025-01-20 Carlos Alegría-Galicia , David Orden , Carlos Seara , Jorge Urrutia

We analyze the correctness of an O(n log n) time divide-and-conquer algorithm for the convex hull problem when each input point is a location determined by a normal distribution. We show that the algorithm finds the convex hull of such…

Computational Geometry · Computer Science 2016-08-08 F. Betul Atalay , Sorelle A. Friedler , Dianna Xu

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

An arrangement of $n$ curves in the plane is given. The query is a point $q$ and the goal is to find the face of the arrangement that contains $q$. A data-structure for point-location, preprocesses the curves into a data structure of…

Computational Geometry · Computer Science 2020-12-07 Sepideh Aghamolaei , Mohammad Ghodsi

High-order methods for convex and nonconvex optimization, particularly $p$th-order Adaptive Regularization Methods (AR$p$), have attracted significant research interest by naturally incorporating high-order Taylor models into adaptive…

Optimization and Control · Mathematics 2025-04-30 Wenqi Zhu , Coralia Cartis

An algorithm which computes a solution of a set optimization problem is provided. The graph of the objective map is assumed to be given by finitely many linear inequalities. A solution is understood to be a set of points in the domain…

Optimization and Control · Mathematics 2014-05-29 Andreas Löhne , Carola Schrage

In the imprecise geometry model, the input is an imprecise point set, which is a family of regions $F = (R_1, \ldots,R_n)$, where for each $R_i$ one may retrieve the true point $p_i \in R_i$. By preprocessing $F$, we can construct the…

Packing optimization is a prevalent problem that necessitates robust and efficient algorithms that are also simple to implement. One group of approaches is the raster methods, which rely on approximating the objects with pixelated…

Computational Geometry · Computer Science 2020-12-10 Gokhan Serhat

In this paper, we first consider the subpath convex hull query problem: Given a simple path $\pi$ of $n$ vertices, preprocess it so that the convex hull of any query subpath of $\pi$ can be quickly obtained. Previously, Guibas, Hershberger,…

Computational Geometry · Computer Science 2020-02-26 Haitao Wang

A new algorithm for regret minimization in online convex optimization is described. The regret of the algorithm after $T$ time periods is $O(\sqrt{T \log T})$ - which is the minimum possible up to a logarithmic term. In addition, the new…

Machine Learning · Computer Science 2023-07-24 Elad Hazan , Nimrod Megiddo