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We develop a Glivenko--Cantelli theory for monotone, almost additive functions of i.\,i.\,d.\ sequences of random variables indexed by~$\Z^d$. Under certain conditions on the random sequence, short range correlations are allowed as well. We…

Probability · Mathematics 2018-09-28 Christoph Schumacher , Fabian Schwarzenberger , Ivan Veselic

Positive $T$-martingales were developed as a general framework that extends the positive measure-valued martingales and are meant to model intermittent turbulence. We extend their scope by allowing the martingale to take complex values. We…

Probability · Mathematics 2016-08-14 Julien Barral , Xiong Jin , Benoît Mandelbrot

The aim of this paper is to develop tractable large deviation approximations for the empirical measure of a small noise diffusion. The starting point is the Freidlin-Wentzell theory, which shows how to approximate via a large deviation…

Probability · Mathematics 2021-01-11 Paul Dupuis , Guo-Jhen Wu

The theory of error-correcting codes is concerned with constructing codes that optimize simultaneously transmission rate and relative minimum distance. These conflicting requirements determine an asymptotic bound, which is a continuous…

Information Theory · Computer Science 2009-10-28 Yuri I. Manin , Matilde Marcolli

The quality of numerical computations can be measured through their forward error, for which finding good error bounds is challenging in general. For several algorithms and using stochastic rounding (SR), probabilistic analysis has been…

Computation · Statistics 2025-08-29 Pablo de Oliveira Castro , El-Mehdi El Arar , Eric Petit , Devan Sohier

Achieving error rates that meet or exceed the fault-tolerance threshold is a central goal for quantum computing experiments, and measuring these error rates using randomized benchmarking is now routine. However, direct comparison between…

Quantum Physics · Physics 2016-10-26 Richard Kueng , David M. Long , Andrew C. Doherty , Steven T. Flammia

The purpose of the present paper is to establish moderate deviation principles for a rather general class of random variables fulfilling certain bounds of the cumulants. We apply a celebrated lemma of the theory of large deviations…

Probability · Mathematics 2012-09-28 Hanna Doering , Peter Eichelsbacher

In this paper, we give explicit rates in the central limit theorem and in the almost sure invariance principle for general R d-valued cocycles that appear in the study of the left random walk on linear groups. Our method of proof lies on a…

Probability · Mathematics 2019-09-19 Christophe Cuny , Jérôme Dedecker , Florence Merlevède

The specific relative entropy, introduced by N. Gantert, allows to quantify the discrepancy between the laws of potentially mutually singular measures. It appears naturally as the large deviations rate function in a randomized version of…

Probability · Mathematics 2023-09-12 Julio Backhoff-Veraguas , Clara Unterberger

This paper develops techniques to study the number of descents in random permutations via martingales. We relax an assumption in the Berry-Esseen theorem of Bolthausen (1982) to extend the theorem's scope to martingale differences of…

Probability · Mathematics 2021-03-16 Alperen Y. Özdemir

In multiparameter quantum estimation, the optimal measurements for different parameters encoded in a quantum state are in general incompatible, giving rise to nontrivial tradeoffs between their attainable precisions. Understanding and…

Quantum Physics · Physics 2026-05-26 Lingna Wang , Hongzhen Chen , Haidong Yuan

Time to event outcomes are often evaluated on the hazard scale, but interpreting hazards may be difficult. Recently, there has been concern in the causal inference literature that hazards actually have a built in selection-effect that…

Methodology · Statistics 2020-02-07 Pål Christie Ryalen , Mats Julius Stensrud , Kjetil Røysland

This paper introduces a martingale that characterizes two properties of evolving forecast distributions. Ideal forecasts of a future event behave as martingales, sequen- tially updating the forecast to leverage the available information as…

Machine Learning · Computer Science 2021-05-17 Dean P. Foster , Robert A. Stine

In this paper, we obtain almost sure invariance principles with rate of order $n^{1/p}\log^\beta n$, $2< p\le 4$, for sums associated to a sequence of reverse martingale differences. Then, we apply those results to obtain similar…

Probability · Mathematics 2012-09-18 Christophe Cuny , Florence Merlevede

U-statistics play central roles in many statistical learning tools but face the haunting issue of scalability. Significant efforts have been devoted into accelerating computation by U-statistic reduction. However, existing results almost…

Methodology · Statistics 2023-06-07 Meijia Shao , Dong Xia , Yuan Zhang

We prove an elementary yet useful inequality bounding the maximal value of certain linear programs. This leads directly to a bound on the martingale difference for arbitrarily dependent random variables, providing a generalization of some…

Functional Analysis · Mathematics 2007-05-23 Leonid Kontorovich

Let $(Z_n)$ be a supercritical branching process in a random environment $\xi$. We study the convergence rates of the martingale $W_n = Z_n/ E[Z_n| \xi]$ to its limit $W$. The following results about the convergence almost sur (a.s.), in…

Probability · Mathematics 2013-02-19 Chunmao Huang , Quansheng Liu

We deduce the asymptotic error distribution of the Euler method for the nonlinear filtering problem with continuous-time observations. Previous works by several authors have shown that the error structure of the method is characterized by…

Probability · Mathematics 2018-09-10 Teppei Ogihara , Hideyuki Tanaka

In this paper, we obtain stability results for martingale representations in a very general framework. More specifically, we consider a sequence of martingales each adapted to its own filtration, and a sequence of random variables…

Probability · Mathematics 2022-06-06 Antonis Papapantoleon , Dylan Possamai , Alexandros Saplaouras

Due to their heterogeneity, insurance risks can be properly described as a mixture of different fixed models, where the weights assigned to each model may be estimated empirically from a sample of available data. If a risk measure is…

Risk Management · Quantitative Finance 2018-02-12 Valeria Bignozzi , Claudio Macci , Lea Petrella