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Related papers: Lower bounds for k-distance approximation

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We present an improved algorithm for {\em quasi-properly} learning convex polyhedra in the realizable PAC setting from data with a margin. Our learning algorithm constructs a consistent polyhedron as an intersection of about $t \log t$…

Machine Learning · Computer Science 2021-11-03 Lee-Ad Gottlieb , Eran Kaufman , Aryeh Kontorovich , Gabriel Nivasch

Let $K$ be a convex body in $\mathbb{R}^d$ which slides freely in a ball. Let $K^{(n)}$ denote the intersection of $n$ closed half-spaces containing $K$ whose bounding hyperplanes are independent and identically distributed according to a…

Metric Geometry · Mathematics 2015-12-09 Ferenc Fodor , Daniel Hug , Ines Ziebarth

We show that a $d$-dimensional polyhedron $S$ in $\real^d$ can be represented by $d$-polynomial inequalities, that is, $S = \{x \in \real^d : p_0(x) \ge 0, >..., p_{d-1}(x) \ge 0 \}$, where $p_0,...,p_{d-1}$ are appropriate polynomials.…

Algebraic Geometry · Mathematics 2010-02-05 Gennadiy Averkov , Ludwig Bröcker

We revisit the moving least squares (MLS) approximation scheme on the sphere $\mathbb S^{d-1} \subset \mathbb R^d$, where $d>1$. It is well known that using the spherical harmonics up to degree $L \in \mathbb N$ as ansatz space yields for…

Numerical Analysis · Mathematics 2024-10-25 Ralf Hielscher , Tim Pöschl

We study "distance spheres": the set of points lying at constant distance from a fixed arbitrary subset $K$ of $[0,1]^d$. We show that, away from the regions where $K$ is "too dense" and a set of small volume, we can decompose $[0,1]^d$…

Classical Analysis and ODEs · Mathematics 2021-07-21 Guy C. David , McKenna Kaczanowski , Dallas Pinkerton

The subspace approximation problem Subspace($k$,$p$) asks for a $k$-dimensional linear subspace that fits a given set of points optimally, where the error for fitting is a generalization of the least squares fit and uses the $\ell_{p}$ norm…

Data Structures and Algorithms · Computer Science 2011-01-04 Amit Deshpande , Kasturi Varadarajan , Madhur Tulsiani , Nisheeth K. Vishnoi

We prove lower bounds on the error incurred when approximating any oscillating function using piecewise polynomial spaces. The estimates are explicit in the polynomial degree and have optimal dependence on the meshwidth and frequency when…

Numerical Analysis · Mathematics 2024-12-05 Jeffrey Galkowski

Based on a quantitative version of the inverse function theorem and an appropriate saddle-point formulation we derive a quasi-optimal error estimate for the finite element approximation of harmonic maps into spheres with a nodal…

Numerical Analysis · Mathematics 2022-09-27 Sören Bartels , Christian Palus , Zhangxian Wang

Distance function to a compact set plays a central role in several areas of computational geometry. Methods that rely on it are robust to the perturbations of the data by the Hausdorff noise, but fail in the presence of outliers. The…

Computational Geometry · Computer Science 2011-02-25 Leonidas J. Guibas , Quentin Mérigot , Dmitriy Morozov

In this paper we investigate the Erd\"os/Falconer distance conjecture for a natural class of sets statistically, though not necessarily arithmetically, similar to a lattice. We prove a good upper bound for spherical means that have been…

Classical Analysis and ODEs · Mathematics 2007-05-23 Alex Iosevich , Misha Rudnev

We prove that any length metric space homeomorphic to a 2-manifold with boundary, also called a length surface, is the Gromov-Hausdorff limit of polyhedral surfaces with controlled geometry. As an application, using the classical…

Metric Geometry · Mathematics 2023-08-03 Dimitrios Ntalampekos , Matthew Romney

We derive upper and lower bounds on the gradients of Wachspress coordinates defined over any simple convex d-dimensional polytope P. The bounds are in terms of a single geometric quantity h_*, which denotes the minimum distance between a…

Numerical Analysis · Mathematics 2022-02-22 Michael Floater , Andrew Gillette , N. Sukumar

We study the problem of $k$-means clustering in the space of straight-line segments in $\mathbb{R}^{2}$ under the Hausdorff distance. For this problem, we give a $(1+\epsilon)$-approximation algorithm that, for an input of $n$ segments, for…

Computational Geometry · Computer Science 2023-05-19 Sergio Cabello , Panos Giannopoulos

Let $\mu_N$ be the empirical measure associated to a $N$-sample of a given probability distribution $\mu$ on $\mathbb{R}^d$. We are interested in the rate of convergence of $\mu_N$ to $\mu$, when measured in the Wasserstein distance of…

Probability · Mathematics 2013-12-10 Nicolas Fournier , Arnaud Guillin

We compute the Hausdorff dimension of the set of simultaneously $q^{-\lambda}$-well approximable points on the Veronese curve in $\mathbb{R}^n$ for $\lambda$ between $\frac{1}{n}$ and $\frac{2}{2n-1}$. For $n=3$, the same result is given…

Number Theory · Mathematics 2025-03-14 Dzmitry Badziahin

In the polytope membership problem, a convex polytope $K$ in $\mathbb{R}^d$ is given, and the objective is to preprocess $K$ into a data structure so that, given any query point $q \in \mathbb{R}^d$, it is possible to determine efficiently…

Computational Geometry · Computer Science 2018-01-11 Sunil Arya , Guilherme D. da Fonseca , David M. Mount

In this paper we present some bounds of Hausdorff measures of objects definable in o-minimal structures: sets, fibers of maps, inverse images of curves of maps, etc. Moreover, we also give some explicit bounds for semi-algebraic or…

Differential Geometry · Mathematics 2012-04-27 Ta Le Loi , Phan Phien

We show that in any $d$-dimensional real normed space, unit balls can be packed with density at least \[\frac{(1-o(1))d\log d}{2^{d+1}},\] improving a result of Schmidt from 1958 by a logarithmic factor and generalizing the recent result of…

Metric Geometry · Mathematics 2025-04-23 Carl Schildkraut

We show that an $n$-dimensional surface whose entropy is close to that of an $n$-dimensional plane is close in Hausdorff distance to some $n$-dimensional plane at every scale. Moreover we show that self-expanders of low entropy converge in…

Differential Geometry · Mathematics 2020-03-18 Letian Chen

A novel algorithm is proposed for quantitative comparisons between compact surfaces embedded in the three-dimensional Euclidian space. The key idea is to identify those objects with the associated surface measures and compute a weak…

Numerical Analysis · Mathematics 2024-01-17 Kazuki Koga