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The k-d tree was one of the first spatial data structures proposed for nearest neighbor search. Its efficacy is diminished in high-dimensional spaces, but several variants, with randomization and overlapping cells, have proved to be…

Data Structures and Algorithms · Computer Science 2013-02-11 Sanjoy Dasgupta , Kaushik Sinha

We study the problem of estimating multivariate log-concave probability density functions. We prove the first sample complexity upper bound for learning log-concave densities on $\mathbb{R}^d$, for all $d \geq 1$. Prior to our work, no…

Machine Learning · Computer Science 2017-06-07 Ilias Diakonikolas , Daniel M. Kane , Alistair Stewart

George R. Terrell (1983, {Ann. Probab., vol. 11(3), pp. 823--826) showed that the Pearson coefficient of correlation of an ordered pair from a random sample of size two is at most one-half, and the equality is attained only for rectangular…

Probability · Mathematics 2022-05-31 Nickos Papadatos

We study the asymptotic behavior of the diameter or maximum interpoint distance of a cloud of i.i.d. $d$-dimensional random vectors when the number of points in the cloud tends to infinity. This is a non standard extreme value problem since…

Probability · Mathematics 2017-11-30 Yann Demichel , Ana Karina Fermin , Philippe Soulier

Decisions are often based on imprecise, uncertain or vague information. Likewise, the consequences of an action are often equally unpredictable, thus putting the decision maker into a twofold jeopardy. Assuming that the effects of an action…

General Economics · Economics 2022-05-03 Stefan Rass , Sandra König , Stefan Schauer

Twisted hypercubes are generalizations of the Boolean hypercube, obtained by iteratively connecting two instances of a graph by a uniformly random perfect matching. Dudek et al. showed that when the two instances are independent, these…

Combinatorics · Mathematics 2023-05-08 Itai Benjamini , Yotam Dikstein , Renan Gross , Maksim Zhukovskii

Random forests, introduced by Leo Breiman in 2001, are a very effective statistical method. The complex mechanism of the method makes theoretical analysis difficult. Therefore, a simplified version of random forests, called purely random…

Statistics Theory · Mathematics 2010-07-28 Robin Genuer

The proof of the theorem, which states that the Euclidean metric on the set of random points in an $n$-dimensional Euclidean space with the distribution of a special class, converges in probability in the limit $n\rightarrow\infty$ to the…

Mathematical Physics · Physics 2014-04-22 Alexander P. Zubarev

We prove a conjecture by Garbe et al. [arXiv:2010.07854] by showing that a Latin square is quasirandom if and only if the density of every 2x3 pattern is 1/720+o(1). This result is the best possible in the sense that 2x3 cannot be replaced…

Combinatorics · Mathematics 2021-08-27 Jacob W. Cooper , Daniel Kral , Ander Lamaison , Samuel Mohr

Many questions about triangles and quadrilaterals with rational sides, diagonals and areas can be reduced to solving certain Diophantine equations. We look at a number of such questions including the question of approximating arbitrary…

Number Theory · Mathematics 2017-05-08 C. P. Anil Kumar

Santal\'o calculated the measures for all positions of a moving line segment in which it lies inside a fixed circle and intersects this circle in one or two points. From these measures he concluded hitting probabilities for a line segment…

Metric Geometry · Mathematics 2019-05-08 Uwe Bäsel

Consider a random set of points on the unit sphere in $\mathbb{R}^d$, which can be either uniformly sampled or a Poisson point process. Its convex hull is a random inscribed polytope, whose boundary approximates the sphere. We focus on the…

Metric Geometry · Mathematics 2020-07-16 Arseniy Akopyan , Herbert Edelsbrunner , Anton Nikitenko

The Johnson-Lindenstrauss (JL) theorem states that a set of points in high-dimensional space can be embedded into a lower-dimensional space while approximately preserving pairwise distances with high probability Johnson and Lindenstrauss…

Data Structures and Algorithms · Computer Science 2026-01-01 Pierre Mackenzie

A widely investigated subject in combinatorial geometry, originated from Erd\H{o}s, is the following. Given a point set $P$ of cardinality $n$ in the plane, how can we describe the distribution of the determined distances? This has been…

Consider a random multigraph G* with given vertex degrees d_1,...,d_n, contructed by the configuration model. We show that, asymptotically for a sequence of such multigraphs with the number of edges (d_1+...+d_n)/2 tending to infinity, the…

Combinatorics · Mathematics 2007-05-23 Svante Janson

Simple random coverage models, well studied in Euclidean space, can also be defined on a general compact metric space. By analogy with the geometric models, and with the discrete coupon collector's problem and with cover times for finite…

Probability · Mathematics 2021-02-01 David J. Aldous

We consider the space of complete and separable metric spaces which are equipped with a probability measure. A notion of convergence is given based on the philosophy that a sequence of metric measure spaces converges if and only if all…

Probability · Mathematics 2008-06-13 Andreas Greven , Peter Pfaffelhuber , Anita Winter

To generate a triangle of unit perimeter, break a stick of length 1 in two places at random, with the condition that triangle inequalities are satisfied. Is there a similarly natural method for generating triangles of unit area? Study of a…

Probability · Mathematics 2014-12-22 Steven R. Finch

We examine how the measure and the number of vertices of the convex hull of a random sample of $n$ points from an arbitrary probability measure in $\mathbf{R}^d$ relates to the wet part of that measure. This extends classical results for…

Probability · Mathematics 2020-10-13 Imre Bárány , Matthieu Fradelizi , Xavier Goaoc , Alfredo Hubard , Günter Rote

As observers of the universe we are physical systems within it. If the universe is very large in space and/or time, the probability becomes significant that the data on which we base predictions is replicated at other locations in…

High Energy Physics - Theory · Physics 2015-05-18 Mark Srednicki , James Hartle
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