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We study sets defined as the intersection of a rank-1 constraint with different choices of linear side constraints. We identify different conditions on the linear side constraints, under which the convex hull of the rank-1 set is polyhedral…

Optimization and Control · Mathematics 2019-09-20 Santanu S. Dey , Burak Kocuk , Asteroide Santana

This paper describes a procedure for a realistic estimation of the number of iterations in the main loop of a recent particle detection algorithm from [1]. The calculations are based on a Monte Carlo simulation of the ATLAS inner detector.…

Instrumentation and Detectors · Physics 2024-02-13 Kacper Topolnicki , Tomasz Bold

We study the maximum weight convex polytope problem, in which the goal is to find a convex polytope maximizing the total weight of enclosed points. Prior to this work, the only known result for this problem was an $O(n^3)$ algorithm for the…

Computational Geometry · Computer Science 2022-07-27 Mohammad Ali Abam , Ali Mohammad Lavasani , Denis Pankratov

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

By solving a problem regarding polynomials in a quotient ring, we obtain the relative hull and the Hermitian hull of projective Reed-Muller codes over the projective plane. The dimension of the hull determines the minimum number of…

Information Theory · Computer Science 2025-03-03 Diego Ruano , Rodrigo San-José

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

Mixed integer set representations, and specifically hybrid zonotopes, have enabled new techniques for reachability and verification of nonlinear and hybrid systems. Mixed-integer sets which have the property that their convex relaxation is…

Systems and Control · Electrical Eng. & Systems 2025-07-17 Jonah J. Glunt , Joshua A. Robbins , Jacob A. Siefert , Daniel Silvestre , Herschel C. Pangborn

We consider asymmetric convex intersection testing (ACIT). Let $P \subset \mathbb{R}^d$ be a set of $n$ points and $\mathcal{H}$ a set of $n$ halfspaces in $d$ dimensions. We denote by $\text{ch}(P)$ the polytope obtained by taking the…

Computational Geometry · Computer Science 2018-08-21 Luis Barba , Wolfgang Mulzer

We prove that the rank-one convex hull of finitely many $2\times 2$ triangular matrices is a semialgebraic set, defined by linear and quadratic polynomials. We present explicit constructions for five-point configurations and offer evidence…

Metric Geometry · Mathematics 2025-09-10 Chiara Meroni , Bogdan Raita

This paper studies the straight skeleton of polyhedra in three dimensions. We first address voxel-based polyhedra (polycubes), formed as the union of a collection of cubical (axis-aligned) voxels. We analyze the ways in which the skeleton…

Computational Geometry · Computer Science 2008-05-02 Gill Barequet , David Eppstein , Michael T. Goodrich , Amir Vaxman

This paper presents rigorous forward error bounds for linear conic optimization problems. The error bounds are formulated in a quite general framework; the underlying vector spaces are not required to be finite-dimensional, and the convex…

Optimization and Control · Mathematics 2007-07-31 Christian Jansson

We provide two algorithms for computing the volume of a convex polytope with half-space representation {x>=0; Ax <=b} for some (m,n) matrix A and some m-vector b. Both algorithms have a O(n^m) computational complexity which makes them…

Numerical Analysis · Mathematics 2025-10-20 J. B. Lasserre , E. S. Zeron

We propose a new algorithm to the problem of polygonal curve approximation based on a multiresolution approach. This algorithm is suboptimal but still maintains some optimality between successive levels of resolution using dynamic…

Computer Vision and Pattern Recognition · Computer Science 2007-05-23 Pierre-François Marteau , Gilbas Ménier

We introduce machine learning methodology to the study of lattice polytopes. With supervised learning techniques, we predict standard properties such as volume, dual volume, reflexivity, etc, with accuracies up to 100%. We focus on 2d…

Linear optimization is many times algorithmically simpler than non-linear convex optimization. Linear optimization over matroid polytopes, matching polytopes and path polytopes are example of problems for which we have simple and efficient…

Machine Learning · Computer Science 2015-08-17 Dan Garber , Elad Hazan

This paper gives a note on an application of the enclosure method to an inverse obstacle scattering problem governed by the Helmholtz equation in two dimensions. It is shown that one can uniquely determine the convex hull of an unknown…

Analysis of PDEs · Mathematics 2011-09-21 Masaru Ikehata

An effective strategy for accelerating the calculation of convex hulls for point sets is to filter the input points by discarding interior points. In this paper, we present such a straightforward and efficient preprocessing approach by…

Computational Geometry · Computer Science 2014-05-30 Gang Mei

We present a novel relaxation framework for general mixed-integer nonlinear programming (MINLP) grounded in computational geometry. Our approach constructs polyhedral relaxations by convexifying finite sets of strategically chosen points,…

Optimization and Control · Mathematics 2026-03-20 Haisheng Zhu , Taotao He , Mohit Tawarmalani

In this article, we determine the amortized computational complexity of the planar dynamic convex hull problem by querying. We present a data structure that maintains a set of n points in the plane under the insertion and deletion of points…

Computational Geometry · Computer Science 2019-03-01 Riko Jacob , Gerth Stølting Brodal

Low-rank matrix recovery problems are inverse problems which naturally arise in various fields like signal processing, imaging and machine learning. They are non-convex and NP-hard in full generality. It is therefore a delicate problem to…

Optimization and Control · Mathematics 2021-05-24 Irène Waldspurger
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