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We derive explicit formulae for the expected volume and the expected number of facets of the convex hull of several multidimensional Gaussian random walks in terms of the Gaussian persistence probabilities. Special cases include the already…

Probability · Mathematics 2020-12-25 Julien Randon-Furling , Dmitry Zaporozhets

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

Let $P$ be a set of $n$ points in the plane. We consider a variation of the classical Erd\H{o}s-Szekeres problem, presenting efficient algorithms with $O(n^3)$ running time and $O(n^2)$ space complexity that compute: (1) A subset $S$ of $P$…

Computational Geometry · Computer Science 2024-12-18 Hernán González-Aguilar , David Orden , Pablo Pérez-Lantero , David Rappaport , Carlos Seara , Javier Tejel , Jorge Urrutia

Finding the coordinate-wise maxima and the convex hull of a planar point set are probably the most classic problems in computational geometry. We consider these problems in the self-improving setting. Here, we have $n$ distributions…

Computational Geometry · Computer Science 2014-04-29 Kenneth L. Clarkson , Wolfgang Mulzer , C. Seshadhri

In this paper, we study the linear separability problem for stochastic geometric objects under the well-known unipoint/multipoint uncertainty models. Let $S=S_R \cup S_B$ be a given set of stochastic bichromatic points, and define $n =…

Computational Geometry · Computer Science 2016-04-06 Jie Xue , Yuan Li , Ravi Janardan

We study the convex-hull problem in a probabilistic setting, motivated by the need to handle data uncertainty inherent in many applications, including sensor databases, location-based services and computer vision. In our framework, the…

Computational Geometry · Computer Science 2014-06-26 Pankaj K. Agarwal , Sariel Har-Peled , Subhash Suri , Hakan Yildiz , Wuzhou Zhang

We consider the population Wasserstein barycenter problem for random probability measures supported on a finite set of points and generated by an online stream of data. This leads to a complicated stochastic optimization problem where the…

Optimization and Control · Mathematics 2021-12-06 Daniil Tiapkin , Alexander Gasnikov , Pavel Dvurechensky

In this paper, we study the problem of computing a minimum-width axis-aligned cubic shell that encloses a given set of $n$ points in a three-dimensional space. A cubic shell is a closed volume between two concentric and face-parallel cubes.…

Computational Geometry · Computer Science 2019-04-16 Sang Won Bae

Randomized clinical trials eliminate confounding but impose strict exclusion criteria that limit recruitment to a subset of the population. Observational datasets are more inclusive but suffer from confounding -- often providing overly…

Machine Learning · Statistics 2022-10-31 Eric V. Strobl , Thomas A. Lasko

In this paper, we present Ray-shooting Quickhull, which is a simple, randomized, outputsensitive version of the Quickhull algorithm for constructing the convex hull of a set of n points in the plane. We show that the randomized Ray-shooting…

Computational Geometry · Computer Science 2024-10-01 Michael T. Goodrich , Ryuto Kitagawa

Necessary and sufficient conditions for the square-integrability of recently proposed unbiased estimators are established. A geometric characterization of a distribution that optimizes the performance of these estimators is given. An…

Statistics Theory · Mathematics 2019-09-09 Nabil Kahale

We study the problem of approximating the mixed volume $V(P_1^{(\alpha_1)}, \dots, P_k^{(\alpha_k)})$ of an $k$-tuple of convex polytopes $(P_1, \dots, P_k)$, each of which is defined as the convex hull of at most $m_0$ points in…

Computational Geometry · Computer Science 2025-12-30 Hariharan Narayanan , Sourav Roy

This paper presents an alternate choice of computing the convex hulls (CHs) for planar point sets. We firstly discard the interior points and then sort the remaining vertices by x- / y- coordinates separately, and later create a group…

Computational Geometry · Computer Science 2013-09-02 Gang Mei , John C. Tipper , Nengxiong Xu

Many classical algorithms are known for computing the convex hull of a set of $n$ point in $\mathbb{R}^2$ using $O(n)$ space. For large point sets, whose size exceeds the size of the working space, these algorithms cannot be directly used.…

Computational Geometry · Computer Science 2018-10-02 Martin Farach-Colton , Meng Li , Meng-Tsung Tsai

Let $X_1,\ldots,X_n$ be i.i.d.\ random points in the $d$-dimensional Euclidean space sampled according to one of the following probability densities: $$ f_{d,\beta} (x) = \text{const} \cdot (1-\|x\|^2)^{\beta}, \quad \|x\|\leq 1, \quad…

Metric Geometry · Mathematics 2017-12-22 Zakhar Kabluchko , Daniel Temesvari , Christoph Thaele

We study the polyhedral structure of the static probabilistic lot-sizing problem and propose valid inequalities that integrate information from the chance constraint and the binary setup variables. We prove that the proposed inequalities…

Optimization and Control · Mathematics 2020-06-02 Xiao Liu , Simge Kucukyavuz

We study the convex hulls of reachable sets of nonlinear systems with bounded disturbances and uncertain initial conditions. Reachable sets play a critical role in control, but remain notoriously challenging to compute, and existing…

Optimization and Control · Mathematics 2026-04-16 Thomas Lew , Riccardo Bonalli , Marco Pavone

In this paper, we study the problem of computing the diameter of a set of $n$ points in $d$-dimensional Euclidean space for a fixed dimension $d$, and propose a new $(1+\varepsilon)$-approximation algorithm with $O(n+ 1/\varepsilon^{d-1})$…

Computational Geometry · Computer Science 2019-05-08 Mahdi Imanparast , Seyed Naser Hashemi , Ali Mohades

Given a point set $P$ in the plane, we seek a subset $Q\subseteq P$, whose convex hull gives a smaller and thus simpler representation of the convex hull of $P$. Specifically, let $cost(Q,P)$ denote the Hausdorff distance between the convex…

Computational Geometry · Computer Science 2021-10-05 Georgiy Klimenko , Benjamin Raichel

In an ordinary feature selection procedure, a set of important features is obtained by solving an optimization problem such as the Lasso regression problem, and we expect that the obtained features explain the data well. In this study,…

Machine Learning · Statistics 2018-10-16 Satoshi Hara , Takanori Maehara