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Let B be a p-uniformly convex Banach space, with p >= 2. Let T be a linear operator on B, and let A_n x denote the ergodic average (1 / n) sum_{i< n} T^n x. We prove the following variational inequality in the case where T is power bounded…

Dynamical Systems · Mathematics 2015-05-20 Jeremy Avigad , Jason Rute

We introduce the notion of uniform gamma-radonification of a family of operators, which unifies the notions of R-boundedness of a family of operators and gamma-radonification of an individual operator. We study the the properties of…

Functional Analysis · Mathematics 2011-10-20 Bernhard H. Haak , Jan van Neerven

This manuscript considers the problem of learning a random Gaussian network function using a fully connected network with frozen intermediate layers and trainable readout layer. This problem can be seen as a natural generalization of the…

Machine Learning · Statistics 2023-02-02 Dominik Schröder , Hugo Cui , Daniil Dmitriev , Bruno Loureiro

We study random trees which are invariant in law under the operation of contracting each edge independently with probability $p\in(0,1)$. We show that all such trees can be constructed through Poissonian sampling from a certain class of…

Probability · Mathematics 2018-06-20 Olivier Hénard , Pascal Maillard

We consider the anomalous sub-diffusion of a class of Gaussian processes that can be expressed in terms of sums of Ornstein-Uhlenbeck processes. As a generic class of processes, we introduce a single parameter such that for any $\nu \in…

Probability · Mathematics 2009-11-24 Scott A McKinley

We study continuum percolation on certain negatively dependent point processes on \R^2. Specifically, we study the Ginibre ensemble and the planar Gaussian zero process, which are the two main natural models of translation invariant point…

Probability · Mathematics 2012-11-13 Subhro Ghosh , Manjunath Krishnapur , Yuval Peres

Given a finite typed rooted tree $T$ with $n$ vertices, the {\em empirical subtree measure} is the uniform measure on the $n$ typed subtrees of $T$ formed by taking all descendants of a single vertex. We prove a large deviation principle in…

Probability · Mathematics 2007-05-23 Amir Dembo , Peter Morters , Scott Sheffield

In this paper we consider a random graph on which topological restrictions are imposed, such as constraints on the total number of edges, wedges, and triangles. We work in the dense regime, in which the number of edges per vertex scales…

Probability · Mathematics 2018-07-24 F. den Hollander , M. Mandjes , A. Roccaverde , N. J. Starreveld

We study the problem of a random Gaussian vector field given that a particular real quadratic form $\mathcal{Q}$ is arbitrarily large. We prove that in such a case the Gaussian field is primarily governed by the fundamental eigenmode of a…

Mathematical Physics · Physics 2024-03-12 Gargee Sharma

An eigenvalue of the adjacency matrix of a graph is said to be main if the all-ones vector is not orthogonal to its associated eigenspace. A generalized Bethe tree with $k$ levels is a rooted tree in which vertices at the same level have…

Combinatorics · Mathematics 2022-01-05 Zhidan Yan , Wei Wang

The starting point of this work is a theorem due to Maxwell characterizing the distribution of a Gaussian vector with at least two coordinates. We define the Gaussian orthogonal, unitary and symplectic tensor ensembles for notions of real…

Mathematical Physics · Physics 2026-04-02 Rémi Bonnin

We derive a sufficient condition for a sparse graph G on n vertices to contain a copy of a tree T of maximum degree at most d on (1-\epsilon)n vertices, in terms of the expansion properties of G. As a result we show that for fixed d\geq 2…

Combinatorics · Mathematics 2007-06-29 Noga Alon , Michael Krivelevich , Benny Sudakov

Gaussian processes (GPs) are widely-used tools in spatial statistics and machine learning and the formulae for the mean function and covariance kernel of a GP $T u$ that is the image of another GP $u$ under a linear transformation $T$…

Probability · Mathematics 2024-10-08 Tadashi Matsumoto , T. J. Sullivan

Causal discovery aims to recover a causal graph from data generated by it; constraint based methods do so by searching for a d-separating conditioning set of nodes in the graph via an oracle. In this paper, we provide analytic evidence that…

Machine Learning · Computer Science 2023-10-04 Itai Feigenbaum , Huan Wang , Shelby Heinecke , Juan Carlos Niebles , Weiran Yao , Caiming Xiong , Devansh Arpit

A model of the passive vector quantity advected by a Gaussian time-decorrelated self-similar velocity field is studied; the effects of pressure and large-scale anisotropy are discussed. The inertial-range behavior of the pair correlation…

Chaotic Dynamics · Physics 2009-11-07 L. Ts. Adzhemyan , N. V. Antonov , A. V. Runov

Consider the normalized adjacency matrices of random $d$-regular graphs on $N$ vertices with fixed degree $d\geq3$. We prove that, with probability $1-N^{-1+{\varepsilon}}$ for any ${\varepsilon} >0$, the following two properties hold as $N…

Probability · Mathematics 2025-02-04 Jiaoyang Huang , Horng-Tzer Yau

This monograph resolves - in a dense class of cases - several open problems concerning geodesics in i.i.d. first-passage percolation on $\mathbb{Z}^d$. Our primary interest is in the empirical measures of edge-weights observed along…

Probability · Mathematics 2021-10-04 Erik Bates

We prove that the local limit of the weighted spanning trees on any simple connected high degree almost regular sequence of electric networks is the Poisson(1) branching process conditioned to survive forever, by generalizing [NP22] and…

Probability · Mathematics 2026-01-01 Ágnes Kúsz

Let $T$ be a tree with induced partial order $\preceq$. We investigate centered Gaussian processes $X=(X_t)_{t\in T}$ represented as $$ X_t=\sigma(t)\sum_{v \preceq t}\alpha(v)\xi_v $$ for given weight functions $\alpha$ and $\sigma$ on $T$…

Probability · Mathematics 2012-12-04 Mikhail Lifshits , Werner Linde

In this paper, we present some asymptotic properties of the normalized inverse-Gaussian process. In particular, when the concentration parameter is large, we establish an analogue of the empirical functional central limit theorem, the…

Statistics Theory · Mathematics 2012-06-29 Luai Al Labadi , Mahmoud Zarepour