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In this article we quantify almost sure martingale convergence theorems in terms of the tradeoff between asymptotic almost sure rates of convergence (error tolerance) and the respective modulus of convergence. For this purpose we generalize…

Probability · Mathematics 2025-03-13 Luisa F. Estrada , Michael A. Högele , Alexander Steinicke

This paper introduces a version of decoupling and randomization to establish concentration inequalities for double-indexed permutation statistics. The results yield, among other applications, a new combinatorial Hanson-Wright inequality and…

Statistics Theory · Mathematics 2026-03-23 Mingxuan Zou , Jingfan Xu , Peng Ding , Fang Han

In this note, we improve some concentration inequalities for martingales with bounded increments. These results recover the missing factor in Freedman-style inequalities and are near optimal. We also provide minor refinements of…

Probability · Mathematics 2024-12-31 Arun Kumar Kuchibhotla

We present two alternative ways to apply PAC-Bayesian analysis to sequences of dependent random variables. The first is based on a new lemma that enables to bound expectations of convex functions of certain dependent random variables by…

Machine Learning · Computer Science 2011-05-20 Yevgeny Seldin , François Laviolette , John Shawe-Taylor , Jan Peters , Peter Auer

This work proposes a new exchangeability test for a random sequence through a martingale based approach. Its main contributions include: 1) an additive martingale which is more amenable for designing exchangeability tests by exploiting the…

Statistics Theory · Mathematics 2020-07-27 Liang Dai , Mohamed-Rafik Bouguelia

We derive both Azuma-Hoeffding and Burkholder-type inequalities for partial sums over a rectangular grid of dimension $d$ of a random field satisfying a weak dependency assumption of projective type: the difference between the expectation…

Probability · Mathematics 2023-06-29 Gilles Blanchard , Alexandra Carpentier , Oleksandr Zadorozhnyi

This paper proposes novel tests for the absence of jumps in a univariate semimartingale and for the absence of common jumps in a bivariate semimartingale. Our methods rely on ratio statistics of power variations based on irregular…

Statistics Theory · Mathematics 2017-12-21 Ole Martin , Mathias Vetter

The martingale method is used to establish concentration inequalities for a class of dependent random sequences on a countable state space, with the constants in the inequalities expressed in terms of certain mixing coefficients. Along the…

Probability · Mathematics 2009-01-22 Leonid , Kontorovich , Kavita Ramanan

This paper proposes a novel test for simultaneous jumps in a bivariate It\^o semimartingale when observation times are asynchronous and irregular. Inference is built on a realized correlation coefficient for the jumps of the two processes…

Statistics Theory · Mathematics 2016-06-24 Ole Martin , Mathias Vetter

We derive explicit Bernstein-type and Bennett-type concentration inequalities for matrix-valued martingale processes with unbounded observations from the Hermitian space $\mathbb{H}(d)$. Specifically, we assume that the…

Probability · Mathematics 2025-02-21 Alexey Kroshnin , Alexandra Suvorikova

In this paper we prove exponential inequalities (also called Bernstein's inequality) for fractional martingales. As an immediate corollary, we will discuss weak law of large numbers for fractional martingales under divergence assumption on…

Probability · Mathematics 2012-04-20 Bruno Saussereau

We give concentration bounds for martingales that are uniform over finite times and extend classical Hoeffding and Bernstein inequalities. We also demonstrate our concentration bounds to be optimal with a matching anti-concentration…

Probability · Mathematics 2015-12-03 Akshay Balsubramani

Initially motivated by the study of the non-asymptotic properties of non-parametric tests based on permutation methods, concentration inequalities for uniformly permuted sums have been largely studied in the literature. Recently, Delyon et…

Probability · Mathematics 2018-05-10 Mélisande Albert

This paper develops a new dimension-free Azuma-Hoeffding type bound on summation norm of a martingale difference sequence with random individual bounds. With this novel result, we provide high-probability bounds for the gradient norm…

Machine Learning · Statistics 2024-01-31 Yanjie Zhong , Jiaqi Li , Soumendra Lahiri

We obtain concentration and large deviation for the sums of independent and identically distributed random variables with heavy-tailed distributions. Our concentration results are concerned with random variables whose distributions satisfy…

Probability · Mathematics 2022-07-27 Milad Bakhshizadeh , Arian Maleki , Victor H. de la Pena

Concentration inequalities are widely used for analyzing machine learning algorithms. However, current concentration inequalities cannot be applied to some of the most popular deep neural networks, notably in natural language processing.…

Machine Learning · Statistics 2021-03-22 Rémy Garnier , Raphaël Langhendries

This paper introduces test and estimation procedures for abrupt and gradual changes in the entire jump behaviour of a discretely observed Ito semimartingale. In contrast to existing work we analyse jumps of arbitrary size which are not…

Statistics Theory · Mathematics 2019-02-08 Michael Hoffmann , Holger Dette

This paper concerns with a mathematical modelling of biological experiments, and its influence on our lives. Fractional hybrid iterative differential equations are equations that interested in mathematical model of biology. Our technique is…

Classical Analysis and ODEs · Mathematics 2015-09-29 Rabha W. Ibrahim , Adem Kilicman , Faten H. Damag

Brute force matching of binary image feature descriptors is conventionally performed using the Hamming distance. This paper assesses the use of alternative metrics in order to see whether they can produce feature correspondences that yield…

Computer Vision and Pattern Recognition · Computer Science 2017-04-24 Erkan Bostanci

We derive two probabilistic bounds for the relative forward error in the floating point summation of $n$ real numbers, by representing the roundoffs as independent, zero-mean, bounded random variables. The first probabilistic bound is based…

Numerical Analysis · Mathematics 2021-05-31 Johnathan Rhyne