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Related papers: On weak approximation of U-statistics

200 papers

The notion of weak measurement provides a formalism for extracting information from a quantum system in the limit of vanishing disturbance to its state. Here we extend this formalism to the measurement of sequences of observables. When…

Quantum Physics · Physics 2009-11-13 Graeme Mitchison , Richard Jozsa , Sandu Popescu

U-statistics of spatial point processes given by a density with respect to a Poisson process are investigated. In the first half of the paper general relations are derived for the moments of the functionals using kernels from the Wiener-Ito…

Probability · Mathematics 2014-06-24 Viktor Benes , Marketa Zikmundova

A two-variable stochastic model for diffusion-limited nucleation is developed using a formalism derived from fluctuating hydrodynamics. The model is a direct generalization of the standard Classical Nucleation Theory. The nucleation rate…

Chemical Physics · Physics 2015-05-26 James F. Lutsko , Miguel A. Durán-Olivencia

This article discusses a unified convergence analysis of the semilinear time-dependent equation $\partial_t u + (-1)^\mathrm{m}\Delta^{\mathrm{m}}u + u^3 - u = f$ with $\mathrm{m} \in \{1,2\}$ and homogeneous Dirichlet boundary conditions.…

Analysis of PDEs · Mathematics 2026-05-12 Gopikrishnan Chirappurathu Remesan

Under some mild regularity on the normalizing sequence, we obtain necessary and sufficient conditions for the Strong Law of Large Numbers for (symmetrized) U-statistics. We also obtain nasc's for the a.s. convergence of series of an…

Probability · Mathematics 2014-11-17 Rafał Latała , Joel Zinn

This work is a follow-up to our previous work "A numerical approach related to defect-type theories for some weakly random problems in homogenization" (preprint available on this archive). It extends and complements, both theoretically and…

Analysis of PDEs · Mathematics 2010-05-24 Arnaud Anantharaman , Claude Le Bris

We study asymptotically the twisted second moment of the family of modular $L$-functions to a fixed modulus. As an application, we establish sharp lower bounds for all real $k \geq 0$ and sharp upper bounds for $k$ in the range $0 \leq k…

Number Theory · Mathematics 2025-04-04 Peng Gao , Liangyi Zhao

This paper studies the probabilistic function approximation problem over reproducing kernel Hilbert spaces. We show the existence and uniqueness of the optimizer under mild assumptions. Furthermore, we generalize the celebrated representer…

Functional Analysis · Mathematics 2025-07-16 Dongwei Chen , Kai-Hsiang Wang

Consider a setting with multiple units (e.g., individuals, cohorts, geographic locations) and outcomes (e.g., treatments, times, items), where the goal is to learn a multivariate distribution for each unit-outcome entry, such as the…

Machine Learning · Statistics 2025-10-21 Kyuseong Choi , Jacob Feitelberg , Caleb Chin , Anish Agarwal , Raaz Dwivedi

The authors of a recent paper [Phys. Rev. Lett. 113, 120404 (2014)] suggest that "weak values are not inherently quantum but rather a purely statistical feature of pre- and postselection with disturbance". We argue that this claim is…

Quantum Physics · Physics 2014-10-17 D. Sokolovski

Fractional moments have been investigated by many authors to represent the density of univariate and bivariate random variables in different contexts. Fractional moments are indeed important when the density of the random variable has…

Statistical Mechanics · Physics 2009-11-18 Giulio Cottone , Mario Di Paola , Ralf Metzler

This paper mainly addresses the optimization of $p$-th moment of $\mathbb{R}^n$-valued random variable. Through an ingenious approximation mechanism, one transforms the maximization problem into a sequence of minimization problems, which…

Optimization and Control · Mathematics 2016-07-26 Xiaojun Lu , Yanhua Wu

This paper studies probabilistic dual frames and the associated dual frame potentials from the perspective of optimal mass transport. The main contribution of this work shows that given a probabilistic frame, its associated dual frame…

Functional Analysis · Mathematics 2025-12-05 Dongwei Chen

This paper describes a simple procedure to estimate the parameters of the univariate truncated normal and lognormal distributions by maximum likelihood. It starts from a reparameterization of the lognormal that was previously introduced by…

Computation · Statistics 2014-07-25 Salvador Pueyo

Methods for the reduction of the complexity of computational problems are presented, as well as their connections to renormalization, scaling, and irreversible statistical mechanics. Several statistically stationary cases are analyzed; for…

Numerical Analysis · Mathematics 2007-05-23 Alexandre J. Chorin , Panagiotis Stinis

This thesis consists of two independent parts: random matrices, which form the first one-third of this thesis, and machine learning, which constitutes the remaining part. The main results of this thesis are as follows: a necessary and…

Machine Learning · Statistics 2018-07-26 Sushma Kumari

The Gumbel-Softmax probability distribution allows learning discrete tokens in generative learning, while the Gumbel-Argmax probability distribution is useful in learning discrete structures in discriminative learning. Despite the efforts…

Machine Learning · Computer Science 2024-06-05 Hedda Cohen Indelman , Tamir Hazan

We consider a system of two particles, each with large angular momentum $j$, in the singlet state. The probabilities of finding projections of the angular momenta on selected axes are determined. The generalized Bell inequalities involve…

Quantum Physics · Physics 2019-05-22 M. Kuś , J. Mostowski , J. Pietraszewicz

This article studies the weak convergence and associated Central Limit Theorem for blurring and nonblurring processes. Then, they are applied to the estimation of location parameter. Simulation studies show that the location estimation…

Statistics Theory · Mathematics 2015-01-28 Ting-Li Chen , Hironori Fujisawa , Su-Yun Huang , Chii-Ruey Hwang

We analyze the Nystr\"om approximation of a positive definite kernel associated with a probability measure. We first prove an improved error bound for the conventional Nystr\"om approximation with i.i.d. sampling and singular-value…

Numerical Analysis · Mathematics 2023-05-24 Satoshi Hayakawa , Harald Oberhauser , Terry Lyons
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