English
Related papers

Related papers: Hidden low-discrepancy structures in random point …

200 papers

A very popular class of models for networks posits that each node is represented by a point in a continuous latent space, and that the probability of an edge between nodes is a decreasing function of the distance between them in this latent…

Statistics Theory · Mathematics 2025-01-07 Cosma Rohilla Shalizi , Dena Marie Asta

We consider random energy landscapes constructed from d-dimensional lattices or trees. The distribution of the number of local minima in such landscapes follows a large deviation principle and we derive the associated law exactly for…

Statistical Mechanics · Physics 2009-11-11 Satya N. Majumdar , Olivier C. Martin

The dispersion of a point set in $[0,1]^d$ is the volume of the largest axis parallel box inside the unit cube that does not intersect with the point set. We study the expected dispersion with respect to a random set of $n$ points…

Probability · Mathematics 2020-03-27 Aicke Hinrichs , David Krieg , Robert J. Kunsch , Daniel Rudolf

We study asymptotic lower and upper bounds for the sizes of constant dimension codes with respect to the subspace or injection distance, which is used in random linear network coding. In this context we review known upper bounds and show…

Combinatorics · Mathematics 2017-12-06 Daniel Heinlein , Sascha Kurz

Consider a dataset of n(d) points generated independently from R^d according to a common p.d.f. f_d with support(f_d) = [0,1]^d and sup{f_d([0,1]^d)} growing sub-exponentially in d. We prove that: (i) if n(d) grows sub-exponentially in d,…

Databases · Computer Science 2009-09-01 Chris Giannella

We present deterministic techniques for computing upper and lower bounds on marginal probabilities in sigmoid and noisy-OR networks. These techniques become useful when the size of the network (or clique size) precludes exact computations.…

Artificial Intelligence · Computer Science 2013-02-18 Tommi S. Jaakkola , Michael I. Jordan

We prove that for $c>0$ a sufficiently small universal constant that a random set of $c d^2/\log^4(d)$ independent Gaussian random points in $\mathbb{R}^d$ lie on a common ellipsoid with high probability. This nearly establishes a…

Probability · Mathematics 2022-12-22 Daniel M. Kane , Ilias Diakonikolas

Given a set C in R^d, let p(C) be the probability that a random d-dimensional unimodular lattice, chosen according to Haar measure on SL(d,Z)\SL(d,R), is disjoint from C\{0}. For special convex sets C we prove bounds on p(C) which are sharp…

Number Theory · Mathematics 2014-02-26 Andreas Strömbergsson

Random geometric graphs result from taking $n$ uniformly distributed points in the unit cube, $[0,1]^d$, and connecting two points if their Euclidean distance is at most $r$, for some prescribed $r$. We show that monotone properties for…

Probability · Mathematics 2007-05-23 Ashish Goel , Sanatan Rai , Bhaskar Krishnamachari

We study constrained selection sets of random closed sets defined on a non-atomic probability space. Given a random interval $Y=[y_L,y_U]$ and scalar constraints on the expectation or the median of admissible selections, we characterize the…

Probability · Mathematics 2026-03-20 Arie Beresteanu , Behrooz Moosavi Rameznzadeh

A point set $M$ in $m$-dimensional Euclidean space is called an integral point set if all the distances between the elements of $M$ are integers, and $M$ is not situated on an $(m-1)$-dimensional hyperplane. We improve the linear lower…

Combinatorics · Mathematics 2025-12-02 Nikolai Avdeev

In many interesting situations the size of epsilon-nets depends only on $\epsilon$ together with different complexity measures. The aim of this paper is to give a systematic treatment of such complexity measures arising in Discrete and…

Computational Geometry · Computer Science 2021-01-05 Andrey Kupavskii , Nikita Zhivotovskiy

Consider that the coordinates of $N$ points are randomly generated along the edges of a $d$-dimensional hypercube (random point problem). The probability that an arbitrary point is the $m$th nearest neighbor to its own $n$th nearest…

Disordered Systems and Neural Networks · Physics 2007-05-23 Cesar Augusto Sangaletti Tercariol , Felipe de Mouta Kiipper , Alexandre Souto Martinez

In the Random Subset Sum Problem, given $n$ i.i.d. random variables $X_1, ..., X_n$, we wish to approximate any point $z \in [-1,1]$ as the sum of a suitable subset $X_{i_1(z)}, ..., X_{i_s(z)}$ of them, up to error $\varepsilon$. Despite…

Neural and Evolutionary Computing · Computer Science 2022-11-18 Luca Becchetti , Arthur Carvalho Walraven da Cunha , Andrea Clementi , Francesco d'Amore , Hicham Lesfari , Emanuele Natale , Luca Trevisan

We prove risk bounds for binary classification in high-dimensional settings when the sample size is allowed to be smaller than the dimensionality of the training set observations. In particular, we prove upper bounds for both 'compressive…

Statistics Theory · Mathematics 2017-09-29 Ata Kaban , Robert J. Durrant

Random planar graphs have been the subject of much recent work. Many basic properties of the standard uniform random planar graph P_{n}, by which we mean a graph chosen uniformly at random from the set of all planar graphs with vertex set…

Combinatorics · Mathematics 2013-07-23 Chris Dowden

We imagine an experiment on an unknown quantum mechanical system in which the system is prepared in various ways and a range of measurements are performed. For each measurement M and preparation rho the experimenter can determine, given…

Quantum Physics · Physics 2009-01-20 Stephanie Wehner , Matthias Christandl , Andrew C. Doherty

As the main problem, we consider covering of a $d$-dimensional cube by $n$ balls with reasonably large $d$ (10 or more) and reasonably small $n$, like $n=100$ or $n=1000$. We do not require the full coverage but only 90\% or 95\% coverage.…

Statistics Theory · Mathematics 2020-02-17 Anatoly Zhigljavsky , Jack Noonan

Multiple-choice load balancing has been a topic of intense study since the seminal paper of Azar, Broder, Karlin, and Upfal. Questions in this area can be phrased in terms of orientations of a graph, or more generally a k-uniform random…

Data Structures and Algorithms · Computer Science 2012-02-16 Po-Shen Loh , Rasmus Pagh

The use of random samples to approximate properties of geometric configurations has been an influential idea for both combinatorial and algorithmic purposes. This chapter considers two related notions---$\epsilon$-approximations and…

Computational Geometry · Computer Science 2017-08-09 Nabil H. Mustafa , Kasturi R. Varadarajan