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We consider the set of points in projective $n$-space that generate an extension of degree $e$ over given number field $k$, and deduce an asymptotic formula for the number of such points of absolute height at most $X$, as $X$ tends to…

Number Theory · Mathematics 2012-04-10 Martin Widmer

We explore the notion of degree of asymmetry for integer sequences and related combinatorial objects. The degree of asymmetry is a new combinatorial statistic that measures how far an object is from being symmetric. We define this notion…

Combinatorics · Mathematics 2021-07-14 Sergi Elizalde , Emeric Deutsch

We have developed in the past several algorithms with intrinsic complexity bounds for the problem of point finding in real algebraic varieties. Our aim here is to give a comprehensive presentation of the geometrical tools which are…

Algebraic Geometry · Mathematics 2009-11-23 B. Bank , M. Giusti , J. Heintz , M. Safey El Din , E. Schost

We prove graded bounds on the individual Betti numbers of affine and projective complex varieties. In particular, we give for each $p,d,r$, explicit bounds on the $p$-th Betti numbers of affine and projective subvarieties of $\mathrm{C}^k$,…

Algebraic Geometry · Mathematics 2016-07-20 Saugata Basu , Cordian Riener

Recent literature has shown that symbolic data, such as text and graphs, is often better represented by points on a curved manifold, rather than in Euclidean space. However, geometrical operations on manifolds are generally more complicated…

Machine Learning · Computer Science 2019-02-06 Max Aalto , Nakul Verma

We consider the problem of digitalizing Euclidean segments. Specifically, we look for a constructive method to connect any two points in $\mathbb{Z}^d$. The construction must be {\em consistent} (that is, satisfy the natural extension of…

Computational Geometry · Computer Science 2020-06-30 Man-Kwun Chiu , Matias Korman , Martin Suderland , Takeshi Tokuyama

The classical isoperimetric inequality can be extended to a general normed plane. In the Euclidean plane, the defect in the isoperimetric inequality can be calculated in terms of the signed areas of some singular sets. In this paper we…

Metric Geometry · Mathematics 2020-10-23 Rafael Segadas dos Santos , Marcos Craizer

In this paper we prove, using a refinement of Terracini's Lemma, a sharp lower bound for the degree of (higher) secant varieties to a given projective variety, which extends the well known lower bound for the degree of a variety in terms of…

Algebraic Geometry · Mathematics 2010-09-21 Ciro Ciliberto , Francesco Russo

We calculate the degree of the algebra of covariants $\mathcal{C}_d$ for binary $d$-form. Also, for the degree we obtain its integral representation and asymptotic behavior.

Rings and Algebras · Mathematics 2019-08-27 Leonid Bedratyuk , Nadia Ilash

The degree distribution is an important characteristic of complex networks. In many applications, quantification of degree distribution in the form of a fixed-length feature vector is a necessary step. On the other hand, we often need to…

Social and Information Networks · Computer Science 2013-12-24 Sadegh Aliakbary , Jafar Habibi , Ali Movaghar

A homogeneous set of $n$ points in the $d$-dimensional Euclidean space determines at least $\Omega(n^{2d/(d^2+1)} / \log^{c(d)} n)$ distinct distances for a constant $c(d)>0$. In three-space, we slightly improve our general bound and show…

Combinatorics · Mathematics 2013-12-17 J. Solymosi , Cs. D. Toth

A unified explicit form for difference formulas to approximate the fractional and classical derivatives is presented. The formula gives finite difference approximations for any classical derivatives with a desired order of accuracy at nodal…

Numerical Analysis · Mathematics 2021-05-28 W. A. Gunarathna , H. M. Nasir , W. B. Daundasekera

Let $X \subset \mathbb{C}^{2n}$ be an $n$-dimensional algebraic variety. We define the algebraic version of the generic symmetry defect set (Wigner caustic) of $X$. Moreover, we compute its singularities for $X_d$ being a generic curve of…

Algebraic Geometry · Mathematics 2022-03-08 L. R. G. Dias , M. Farnik , Z. Jelonek

Group-invariant probability distributions appear in many data-generative models in machine learning, such as graphs, point clouds, and images. In practice, one often needs to estimate divergences between such distributions. In this work, we…

Machine Learning · Computer Science 2026-02-05 Behrooz Tahmasebi , Stefanie Jegelka

This paper defines a distance function that measures the dissimilarity between planar geometric figures formed with straight lines. This function can in turn be used in partial matching of different geometric figures. For a given pair of…

Computer Vision and Pattern Recognition · Computer Science 2016-12-06 Apoorva Honnegowda Roopa , Shrisha Rao

A unit spherical Euclidean distance matrix (EDM) D is a matrix whose entries can be realized as the interpoint (squared) Euclidean distances of n points on a unit sphere. In this paper, given such a D and 1 \leq k < l \leq n, we present a…

Metric Geometry · Mathematics 2019-04-09 A. Y. Alfakih

According to a classical result of Spencer, Szemer\'edi, and Trotter (1984), the maximum number of times the unit distance can occur among $n$ points in the plane is $O(n^{4/3})$. This is far from Erd\H{o}s's lower bound, $n^{1+O(1/\log\log…

Combinatorics · Mathematics 2025-07-22 János Pach , Orit E. Raz , József Solymosi

The number of apparent double points of a smooth, irreducible projective variety $X$ of dimension $n$ in $\Proj^{2n+1}$ is the number of secant lines to $X$ passing through the general point of $\Proj^{2n+1}$. This classical notion dates…

Algebraic Geometry · Mathematics 2007-05-23 C. Ciliberto , M. Mella , F. Russo

In the present paper we focus on the coherence properties of general random Euclidean distance matrices, which are very closely related to the respective matrix completion problem. This problem is of great interest in several applications…

Information Theory · Computer Science 2013-05-14 Dionysios S. Kalogerias , Athina P. Petropulu

Kernelized Stein discrepancy (KSD), though being extensively used in goodness-of-fit tests and model learning, suffers from the curse-of-dimensionality. We address this issue by proposing the sliced Stein discrepancy and its scalable and…

Machine Learning · Computer Science 2021-03-18 Wenbo Gong , Yingzhen Li , José Miguel Hernández-Lobato