English
Related papers

Related papers: Set Estimation Under Biconvexity Restrictions

200 papers

Given a random sample of points from some unknown distribution, we propose a new data-driven method for estimating its probability support S. Under the mild assumption that S is r-convex, the smallest r-convex set which contains the sample…

Statistics Theory · Mathematics 2019-07-23 A. Rodríguez-Casal , P. Saavedra-Nieves

We prove that the Hilbert Geometry of a convex set is bi-lipschitz equivalent to a normed vector space if and only if the convex is a polytope.

Differential Geometry · Mathematics 2014-12-10 Constantin Vernicos

Writing an uncomplicated, robust, and scalable three-dimensional convex hull algorithm is challenging and problematic. This includes, coplanar and collinear issues, numerical accuracy, performance, and complexity trade-offs. While there are…

Computational Geometry · Computer Science 2023-04-11 Ben Kenwright

Finite convex geometries are combinatorial structures. It follows from a recent result of M.\ Richter and L.G.\ Rogers that there is an infinite set $T_{rr}$ of planar convex polygons such that $T_{rr}$ with respect to geometric convex…

Combinatorics · Mathematics 2016-08-24 Gábor Czédli , János Kincses

Motivated by set estimation problems, we consider three closely related shape conditions for compact sets: positive reach, r-convexity and rolling condition. First, the relations between these shape conditions are analyzed. Second, we…

Statistics Theory · Mathematics 2011-10-21 Antonio Cuevas , Ricardo Fraiman , Beatriz Pateiro-López

Statistical decision problems lie at the heart of statistical machine learning. The simplest problems are binary and multiclass classification and class probability estimation. Central to their definition is the choice of loss function,…

Machine Learning · Computer Science 2023-08-21 Robert C. Williamson , Zac Cranko

The simplest way to generate a lattice of convex sets is to consider an initial set of points and draw segments, triangles, and any convex hull from it, then intersect them to obtain new points, and so forth. The result is an infinite…

Combinatorics · Mathematics 2024-07-25 Carles Cardó

Vehicle pose estimation with LiDAR is essential in the perception technology of autonomous driving. However, due to incomplete observation measurements and sparsity of the LiDAR point cloud, it is challenging to achieve satisfactory pose…

Computer Vision and Pattern Recognition · Computer Science 2024-02-07 Ningning Ding

Let $D$ be an orientation of a simple graph. Given $u,v\in V(D)$, a directed shortest $(u,v)$-path is a $(u,v)$-geodesic. $S \subseteq V(D)$ is convex if, for every $u,v \in S$, the vertices in each $(u,v)$-geodesic and in each…

Combinatorics · Mathematics 2020-11-24 Julio C. S. Araujo , Pedro S. M. Arraes

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

This paper deals with the regularization of the sum of functions defined on a locally convex spaces through their closed-convex hulls in the bidual space. Different conditions guaranteeing that the closed-convex hull of the sum is the sum…

Optimization and Control · Mathematics 2024-10-11 Rafael Correa , Abderrahim Hantoute , Marco A. López

The standard theory of stochastic approximation (SA) is extended to the case when the constraint set is a Riemannian manifold. Specifically, the standard ODE method for analyzing SA schemes is extended to iterations constrained to stay on a…

Optimization and Control · Mathematics 2017-11-30 Suhail M. Shah

This article studies generalizations of (matrix) convexity, including partial convexity and biconvexity, under the umbrella of $\Gamma$-convexity. Here $\Gamma$ is a tuple of free symmetric polynomials determining the geometry of a…

Operator Algebras · Mathematics 2024-12-19 Igor Klep , Scott McCullough , Tea Štrekelj

Convex sets appear in various mathematical theories, and are used to define notions such as convex functions and hulls. As an abstraction from the usual definition of convex sets in vector spaces, we formalize in Coq an intrinsic…

Logic in Computer Science · Computer Science 2020-05-29 Reynald Affeldt , Jacques Garrigue , Takafumi Saikawa

It is well known that the convex hull of $\{(x,y,xy)\}$, where $(x,y)$ is constrained to lie in a box, is given by the Reformulation-Linearization Technique (RLT) constraints. Belotti {\em et al.\,}(2010) and Miller {\em et al.\,}(2011)…

Optimization and Control · Mathematics 2020-04-16 Kurt M. Anstreicher , Samuel Burer , Kyungchan Park

Convex hulls are useful as tight bounding proxies for a variety of tasks including collision detection, ray intersection, and distance computation. Unfortunately, the complexity of polyhedral convex hulls grows linearly with their input. We…

Graphics · Computer Science 2026-04-17 Alec Jacobson

Similarly to the classic notion in $E^d$, a subset of a positive diameter below $\frac{\pi}{2}$ of a hemisphere of the sphere $S^d$ is called complete, provided adding any extra point increases its diameter. Complete sets are convex bodies…

Metric Geometry · Mathematics 2020-10-08 Marek Lassak

Let n be a positive integer and c an n-tuple of natural numbers. A convex set in Euclidean n-space given by a family of linear relations in the elements of c and depending on their natural order is defined. The extremal elements of this…

Representation Theory · Mathematics 2017-01-20 Anthony Joseph

Necessary and sufficient conditions for convexity and strong convexity, respectively, of sublevel sets that are defined by finitely many real-valued $C^{1,1}$-maps are presented. A novel characterization of strongly convex sets in terms of…

Optimization and Control · Mathematics 2017-01-03 Alexander Weber , Gunther Reissig

Given noisy data, function estimation is considered when the unknown function is known a priori to consist of a small number of regions where the function is either convex or concave. When the number of regions is unknown, the model…

Methodology · Statistics 2019-11-14 Kurt S. Riedel
‹ Prev 1 4 5 6 7 8 10 Next ›