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Given n observations, we study the consistency of a batch of k new observations, in terms of their distribution function. We propose a non-parametric, non-likelihood test based on Edgeworth expansion of the distribution function. The…

Statistics Theory · Mathematics 2009-06-08 Mahendra Mariadassou , Avner Bar-Hen

A Steinhaus random multiplicative function $f$ is a completely multiplicative function obtained by setting its values on primes $f(p)$ to be independent random variables distributed uniformly on the unit circle. Recent work of Harper shows…

Number Theory · Mathematics 2024-01-02 Kannan Soundararajan , Max Wenqiang Xu

We consider the reconstruction of a bandlimited function from its finite localized sample data. Truncating the classical Shannon sampling series results in an unsatisfactory convergence rate due to the slow decay of the sinc function. To…

Numerical Analysis · Mathematics 2018-11-07 Rongrong Lin

Let $x\geq 1$ be a large integer, and let $\mu:\mathbb{N}\longrightarrow\{-1,0,1\}$ be the Mobius function. This article proposes an effective asymptotic result for the autocorrelation function $\sum_{n \leq x} \mu(n) \mu(n+t) =O\left(…

General Mathematics · Mathematics 2023-11-20 N. A. Carella

We study sequences of functions of the form F_p^n -> {0,1} for varying n, and define a notion of convergence based on the induced distributions from restricting the functions to a random affine subspace. Using a decomposition theorem and a…

Combinatorics · Mathematics 2013-08-20 Hamed Hatami , Pooya Hatami , James Hirst

We estimate the concentration functions of $n$-fold convolutions of one-dimensional probability measures. The main result is a supplement to the results of G\"otze and Zaitsev (1998). We show that the estimation of concentration functions…

Probability · Mathematics 2014-02-28 F. Götze , A. Yu. Zaitsev

A new O(N) algorithm based on a recursion method, in which the computational effort is proportional to the number of atoms N, is presented for calculating the inverse of an overlap matrix which is needed in electronic structure calculations…

Condensed Matter · Physics 2016-08-31 T. Ozaki

We consider subtle correlations in the scattering of fluid by randomly placed obstacles, which have been suggested to lead to a diverging dispersion coefficient at long times for high Peclet numbers, in contrast to finite mean-field…

Statistical Mechanics · Physics 2009-11-07 Michael W. Deem , Jeong-Man Park

Consider the sequence of continued fraction convergents $p_n/q_n$ to a random irrational number. We study the distribution of the sequences $p_n \pmod{m}$ and $q_n \pmod{m}$ with a fixed modulus $m$, and more generally, the distribution of…

Dynamical Systems · Mathematics 2025-04-14 Bence Borda

We calculate the triple correlations for the truncated divisor sum $\lambda_{R}(n)$. The $\lambda_{R}(n)$'s behave over certain averages just as the prime counting von Mangoldt function $\Lambda(n)$ does or is conjectured to do. We also…

Number Theory · Mathematics 2007-05-23 D. A. Goldston , C. Y. Yildirim

We devise new algorithms for the single-source shortest paths (SSSP) problem with non-negative edge weights in the CONGEST model of distributed computing. While close-to-optimal solutions, in terms of the number of rounds spent by the…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-08-01 Sebastian Forster , Danupon Nanongkai

We study random normal matrix models whose eigenvalues tend to be distributed within a narrow "band" around the unit circle of width proportional to $\frac1n$, where $n$ is the size of matrices. For general radially symmetric potentials…

Probability · Mathematics 2021-12-22 Sung-Soo Byun , Seong-Mi Seo

The Cramer-Rao-Frechet inequality is reviewed specializing it to track fitting. A diffused opinion attributes to this inequality the limitation of the resolution of the track fits with the number N of observations. It turns out that this…

Instrumentation and Detectors · Physics 2021-10-22 Gregorio Landi , Giovanni E. Landi

By the continuous mapping theorem, if a sequence of $d$-dimensional random vectors $(\mathbf{W}_n)_{n\geq1}$ converges in distribution to a multivariate normal random variable $\Sigma^{1/2}\mathbf{Z}$, then the sequence of random variables…

Probability · Mathematics 2020-03-18 Robert E. Gaunt

Consider $n$ agents connected over a network collaborating to minimize the average of their local cost functions combined with a common nonsmooth function. This paper introduces a unified algorithmic framework for solving such a problem…

Optimization and Control · Mathematics 2026-05-05 Kun Huang , Shi Pu , Angelia Nedić

Belief Propagation (BP) is one of the most popular methods for inference in probabilistic graphical models. BP is guaranteed to return the correct answer for tree structures, but can be incorrect or non-convergent for loopy graphical…

Artificial Intelligence · Computer Science 2012-06-22 Siamak Ravanbakhsh , Chun-Nam Yu , Russell Greiner

Let $\log^Cn\le d\le n/2$ for a sufficiently large constant $C>0$ and let $A_n$ denote the adjacency matrix of a uniform random $d$-regular directed graph on $n$ vertices. We prove that as $n$ tends to infinity, the empirical spectral…

Probability · Mathematics 2017-08-09 Nicholas A. Cook

We describe the component sizes in critical independent p-bond percolation on a random d-regular graph on n vertices, where d \geq 3 is fixed and n grows. We prove mean-field behavior around the critical probability p_c=1/(d-1). In…

Probability · Mathematics 2007-07-24 Asaf Nachmias , Yuval Peres

We derive necessary and sufficient conditions for epi-convergence in distribution of normal integrands. As a basic tool for the proof a new characterisation for distributional convergence of random closed sets is used. Our approach via the…

Probability · Mathematics 2025-07-23 Dietmar Ferger

Discrepancy measures between probability distributions are at the core of statistical inference and machine learning. In many applications, distributions of interest are supported on different spaces, and yet a meaningful correspondence…

Machine Learning · Computer Science 2021-11-23 Zhengxin Zhang , Youssef Mroueh , Ziv Goldfeld , Bharath K. Sriperumbudur
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