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We prove a universality theorem for learning with random features. Our result shows that, in terms of training and generalization errors, a random feature model with a nonlinear activation function is asymptotically equivalent to a…

Information Theory · Computer Science 2022-11-01 Hong Hu , Yue M. Lu

In this paper we present some new limit theorems for power variations of stationary increment L\'{e}vy driven moving average processes. Recently, such asymptotic results have been investigated in [Ann. Probab. 45(6B) (2017), 4477--4528,…

Probability · Mathematics 2018-10-25 Mathias Mørck Ljungdahl , Mark Podolskij

We establish the convergence of the densities of a sequence of nonlinear functionals of an underlying Gaussian process to the density of a Gamma distribution. The key idea of our work is a new density formula for random variables in the…

Probability · Mathematics 2025-11-17 Solesne Bourguin , Thanh Dang , Yaozhong Hu

We establish a central limit theorem for counting large continued fraction digits $(a_n)$, i.e. we count occurrences $\{a_n>b_n\}$, where $(b_n)$ is a sequence of positive integers. Our result improves a similar result by Philipp which…

Probability · Mathematics 2021-12-02 Marc Kesseböhmer , Tanja Schindler

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

In this talk I first review at an elementary level a selection of central limit theorems, including some lesser known cases, for sums and maxima of uncorrelated and correlated random variables. I recall why several of them appear in…

Statistical Mechanics · Physics 2010-08-26 H. J. Hilhorst

We introduce and investigate a new notion of the theory of approximation-the so-called degenerate approximation, i.e. approximation of the function of two (and more) variables (kernel) by means of degenerate function (kernel). We apply…

Probability · Mathematics 2013-03-14 E. Ostrovsky , L. Sirota

We establish finite-dimensional central limit theorems for local, additive, interaction functions of temporally evolving point processes. The dynamics are those of a spatial Poisson process on the flat torus with points subject to a…

Probability · Mathematics 2026-01-26 Efe Onaran , Omer Bobrowski , Robert J. Adler

We establish a multivariate empirical process central limit theorem for stationary $\R^d$-valued stochastic processes $(X_i)_{i\geq 1}$ under very weak conditions concerning the dependence structure of the process. As an application we can…

Probability · Mathematics 2011-01-28 Herold Dehling , Olivier Durieu

We show that the multiple divisor functions of integers in invertible residue classes modulo a prime number, as well as the Fourier coefficients of GL(N) Maass cusp forms for all N larger than 2, satisfy a central limit theorem in a…

Number Theory · Mathematics 2014-06-13 Emmanuel Kowalski , Guillaume Ricotta

Let $G$ be an $N \times N$ real matrix whose entries are independent identically distributed standard normal random variables $G_{ij} \sim \mathcal{N}(0,1)$. The eigenvalues of such matrices are known to form a two-component system…

Probability · Mathematics 2015-12-07 N. J. Simm

In this paper, we establish a spatial central limit theorem for a large class of supercritical branching, not necessarily symmetric, Markov processes with spatially dependent branching mechanisms satisfying a second moment condition. This…

Probability · Mathematics 2014-04-02 Yan-Xia Ren , Renming Song , Rui Zhang

Our principal aim is to observe the Markov discrete-time process of population growth with long-living trajectory. First we study asymptotical decay of generating function of Galton-Watson process for all cases as the Basic Lemma.…

Probability · Mathematics 2020-04-21 Azam A. Imomov

Certain extremum estimators have asymptotic distributions that are non-Gaussian, yet characterizable as the distribution of the $\argmax$ of a Gaussian process. This paper presents high-level sufficient conditions under which such…

Econometrics · Economics 2025-10-24 Matias D. Cattaneo , Gregory Fletcher Cox , Michael Jansson , Kenichi Nagasawa

In this paper, we study central and non-central limit theorems for partial sum of functionals of general stationary Gaussian fields. We apply our result to study drift parameter estimation problems for some stochastic differential equations…

Probability · Mathematics 2015-01-22 Khalifa Es-Sebaiy , Frederi G. Viens

In \cite{BNT}, a framework to prove almost sure central limit theorems for sequences $(G_n)$ belonging to the Wiener space was developed, with a particular emphasis of the case where $G_n$ takes the form of a multiple Wiener-It\^o integral…

Probability · Mathematics 2019-01-21 Ehsan Azmoodeh , Ivan Nourdin

We consider a supercritical general branching population where the lifetimes of individuals are i.i.d. with arbitrary distribution and each individual gives birth to new individuals at Poisson times independently from each others. The…

Probability · Mathematics 2016-11-21 Benoît Henry

We consider two classical ensembles of the random matrix theory: the Wigner matrices and sample covariance matrices, and prove Central Limit Theorem for linear eigenvalue statistics under rather weak (comparing with results known before)…

Mathematical Physics · Physics 2011-01-18 Mariya Shcherbina

In this article we prove large deviations principles for high minima of Gaussian processes with nonnegatively correlated increments on arbitrary intervals. Furthermore, we prove large deviations principles for the increments of such…

Probability · Mathematics 2024-04-08 Zachary Selk

We will prove the Berry-Esseen theorem for the number counting function of the circular $\beta$-ensemble (C$\beta$E), which will imply the central limit theorem for the number of points in arcs of the unit circle in mesoscopic and…

Probability · Mathematics 2023-12-15 Renjie Feng , Gang Tian , Dongyi Wei