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In this paper we introduce a new topological Ramsey space whose elements are infinite ordered polyhedra. Then, we show as an application that the set of finite polyhedra satisfies two types of Ramsey property: one, when viewed as a category…

Combinatorics · Mathematics 2016-02-08 Jose G. Mijares , Gabriel Padilla

This paper is concerned with the hard thresholding operator which sets all but the $k$ largest absolute elements of a vector to zero. We establish a {\em tight} bound to quantitatively characterize the deviation of the thresholded solution…

Machine Learning · Statistics 2020-08-12 Jie Shen , Ping Li

In the statistical inference for long range dependent time series the shape of the limit distribution typically depends on unknown parameters. Therefore, we propose to use subsampling. We show the validity of subsampling for general…

Statistics Theory · Mathematics 2016-10-20 Annika Betken , Martin Wendler

Subgraph counts - in particular the number of occurrences of small shapes such as triangles - characterize properties of random networks, and as a result have seen wide use as network summary statistics. However, subgraphs are typically…

Statistics Theory · Mathematics 2020-06-30 P-A. Maugis

The aim of this paper is twofold. Firstly, we give easy-to-handle criteria to determine whether a given family of subsets of a vector space is a neighbourhood basis of the origin for a complete vector topology. Then, we apply these criteria…

Functional Analysis · Mathematics 2025-02-20 José L. Ansorena , Alejandro Marcos

One of the main questions that arise when studying random and quasi-random structures is which properties P are such that any object that satisfies P "behaves" like a truly random one. In the context of graphs, Chung, Graham, and Wilson…

Combinatorics · Mathematics 2009-03-03 Asaf Shapira , Raphael Yuster

Using the theory of negative association for measures and the notion of random weak limits of sparse graphs, we establish the validity of the cavity method for counting spanning subgraphs subject to local constraints in asymptotically…

Probability · Mathematics 2011-03-21 Justin Salez

We introduce and study a generalized concept of boundedness of a subset of a normed vector space with respect to a cone, which is defined as lower boundedness of the images of the underlying set through all the positive functionals of the…

Optimization and Control · Mathematics 2026-01-13 Marius Durea , Elena-Cristina Stamate

In this survey we describe a recently-developed technique for bounding the number (and controlling the typical structure) of finite objects with forbidden substructures. This technique exploits a subtle clustering phenomenon exhibited by…

Combinatorics · Mathematics 2018-01-16 József Balogh , Robert Morris , Wojciech Samotij

We establish a structure theorem for minimizing sequences for the isoperimetric problem on noncompact $\mathsf{RCD}(K,N)$ spaces $(X,\mathsf{d},\mathcal{H}^N)$. Under the sole (necessary) assumption that the measure of unit balls is…

Differential Geometry · Mathematics 2022-08-30 Gioacchino Antonelli , Stefano Nardulli , Marco Pozzetta

Consider an improper Poisson line process, marked by positive speeds so as to satisfy a scale-invariance property (actually, scale-equivariance). The line process can be characterized by its intensity measure, which belongs to a…

Probability · Mathematics 2014-04-17 Wilfrid S. Kendall

We study the spatial Gibbs random graphs introduced in [MV16] from the point of view of local convergence. These are random graphs embedded in an ambient space consisting of a line segment, defined through a probability measure that favors…

Probability · Mathematics 2017-12-12 Eric Ossami Endo , Daniel Valesin

We study the length of short cycles on uniformly random metric maps (also known as ribbon graphs) of large genus using a Teichm\"uller theory approach. We establish that, as the genus tends to infinity, the length spectrum converges to a…

Probability · Mathematics 2025-04-16 Simon Barazer , Alessandro Giacchetto , Mingkun Liu

The theme of this paper is the derivation of analytic formulae for certain large combinatorial structures. The formulae are obtained via fluid limits of pure jump type Markov processes, established under simple conditions on the Laplace…

Probability · Mathematics 2007-05-23 R. W. R. Darling , J. R. Norris

In a complete metric space that is equipped with a doubling measure and supports a Poincar\'e inequality, we study strict subsets, i.e. sets whose variational capacity with respect to a larger reference set is finite, in the case $p=1$.…

Metric Geometry · Mathematics 2019-03-12 Panu Lahti

We determine the sharp threshold for the containment of all $n$-vertex trees of bounded degree in random geometric graphs with $n$ vertices. This provides a geometric counterpart of Montgomery's threshold result for binomial random graphs,…

Combinatorics · Mathematics 2025-05-23 Michael Anastos , Sahar Diskin , Dawid Ignasiak , Lyuben Lichev , Yetong Sha

In the random geometric graph model $\mathsf{Geo}_d(n,p)$, we identify each of our $n$ vertices with an independently and uniformly sampled vector from the $d$-dimensional unit sphere, and we connect pairs of vertices whose vectors are…

Probability · Mathematics 2021-11-23 Siqi Liu , Sidhanth Mohanty , Tselil Schramm , Elizabeth Yang

Vector spaces over finite fields and Anzahl formulas of subspaces were studied by Wan (Geometry of Classical Groups over Finite Fields, Science Press, 2002). As a generalization, we study vector spaces and singular linear spaces over…

Combinatorics · Mathematics 2025-03-28 Jun Guo , Junli Liu , Qiuli Xu

Background: We study the statistical properties of fragment coverage in genome sequencing experiments. In an extension of the classic Lander-Waterman model, we consider the effect of the length distribution of fragments. We also introduce…

Genomics · Quantitative Biology 2010-05-03 Steven N. Evans , Valerie Hower , Lior Pachter

Statistical analysis of a graph often starts with embedding, the process of representing its nodes as points in space. How to choose the embedding dimension is a nuanced decision in practice, but in theory a notion of true dimension is…

Machine Learning · Statistics 2021-01-06 Patrick Rubin-Delanchy