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In this paper we present the groundwork for an It\^o/Malliavin stochastic calculus and Hida's white noise analysis in the context of a supersymmentry with Z3-graded algebras. To this end we establish a ternary Fock space and the…

Functional Analysis · Mathematics 2022-01-05 Daniel Alpay , Paula Cerejeiras , Uwe Kähler

Stochastic differential equations of Langevin-diffusion form have received significant attention, thanks to their foundational role in both Bayesian sampling algorithms and optimization in machine learning. In the latter, they serve as a…

Optimization and Control · Mathematics 2024-05-14 Fabio V. Difonzo , Vyacheslav Kungurtsev , Jakub Marecek

We consider some reaction-diffusion equations describing systems with the nonlocal consumption of resources and the intraspecific competition. Sharp conditions on the coefficients are obtained to ensure the stability and instability of…

Analysis of PDEs · Mathematics 2024-09-06 Yuming Chen , Vitali Vougalter

If a random variable is not exponentially integrable, it is known that no concentration inequality holds for an infinite sequence of independent copies. Under mild conditions, we establish concentration inequalities for finite sequences of…

Probability · Mathematics 2007-05-23 Franck Barthe , Patrick Cattiaux , Cyril Roberto

We consider a Markov process $X$ associated to a nonnecessarily symmetric Dirichlet form $\mathcal{E}$. We define a stochastic integral with respect to a class of additive functionals of zero quadratic variation and then we obtain an…

Probability · Mathematics 2013-12-18 Alexander Walsh

The note is devoted to estimates for convolutions appearing in some class of stochastic Volterra equations. Two maximal inequalities and exponential tail estimate are proved by the fractional method of infinite dimensional stochastic…

Probability · Mathematics 2007-05-23 Anna Karczewska

We develop the optimal transportation approach to modified log-Sobolev inequalities and to isoperimetric inequalities. Various sufficient conditions for such inequalities are given. Some of them are new even in the classical log-Sobolev…

Probability · Mathematics 2007-09-26 Franck Barthe , Alexander V. Kolesnikov

We study the numerical computation of an expectation of a bounded function with respect to a measure given by a non-normalized density on a convex body. We assume that the density is log-concave, satisfies a variability condition and is not…

Probability · Mathematics 2014-12-03 Daniel Rudolf

In the context of interacting particle systems, we study the influence of the action of the semigroup on the concentration property of Lipschitz functions. As an application, this gives a new approach to estimate the relaxation speed to…

Probability · Mathematics 2015-06-30 Jean René Chazottes , Pierre Collet , Frank Redig

We study stochastic differential equations driven by finite-order chaos processes on abstract Wiener spaces, with pathwise Riemann-Stieltjes integration. The driving noise is an $\mathbb{R}^m$-valued chaotic process given by multiple…

Probability · Mathematics 2026-04-28 Laurent Loosveldt , Yassine Nachit , Ivan Nourdin

We develop a theory of Malliavin calculus for Banach space valued random variables. Using radonifying operators instead of symmetric tensor products we extend the Wiener-Ito isometry to Banach spaces. In the white noise case we obtain two…

Functional Analysis · Mathematics 2008-02-14 Jan Maas

We are concerned with scaling limits of the solutions to stochastic differential equations with stationary coefficients driven by Poisson random measures and Brownian motions. We state an annealed convergence theorem, in which the limit…

Probability · Mathematics 2008-12-26 Remi Rhodes , Vincent Vargas

The problem of sampling according to the probability distribution minimizing a given free energy, using interacting particles unadjusted kinetic Langevin Monte Carlo, is addressed. In this setting, three sources of error arise, related to…

Probability · Mathematics 2024-12-05 Pierre Monmarché , Katharina Schuh

We develop concentration inequalities for the $l_\infty$ norm of vector linear processes with sub-Weibull, mixingale innovations. This inequality is used to obtain a concentration bound for the maximum entrywise norm of the lag-$h$…

Statistics Theory · Mathematics 2024-10-18 Eduardo Fonseca Mendes , Fellipe Lopes

We establish concentration inequalities in the class of ultra log-concave distributions. In particular, we show that ultra log-concave distributions satisfy Poisson concentration bounds. As an application, we derive concentration bounds for…

Probability · Mathematics 2021-10-04 Heshan Aravinda , Arnaud Marsiglietti , James Melbourne

This contribution examines optimization problems that involve stochastic dominance constraints. These problems have uncountably many constraints. We develop methods to solve the optimization problem by reducing the constraints to a finite…

Optimization and Control · Mathematics 2025-02-27 Rajmadan Lakshmanan , Alois Pichler , Miloš Kopa

In this work, we consider rather general and broad class of Markov chains, Ito chains, that look like Euler-Maryama discretization of some Stochastic Differential Equation. The chain we study is a unified framework for theoretical analysis.…

Optimization and Control · Mathematics 2024-04-02 Aleksei Ustimenko , Aleksandr Beznosikov

These notes rigorously construct the stochastic integral of a Hilbert Space valued process driven by a Cylindrical Brownian Motion. We expand upon this stochastic calculus to present an introduction to stochastic differential equations in…

Probability · Mathematics 2023-09-15 Daniel Goodair

The possibility of different interpretations of the stochastic term (or calculi) in the overdamped Langevin equation for the motion of a particle in an inhomogeneous medium is often referred to as the "Ito--Stratonovich dilemma," although…

Statistical Mechanics · Physics 2012-08-28 Hendrick W. de Haan , Mykyta V. Chubynsky , Gary W. Slater

In this paper, we establish maximal concentration bounds for the iterates generated by a stochastic approximation (SA) algorithm under a contractive operator with respect to some arbitrary norm (for example, the $\ell_\infty$-norm). We…

Machine Learning · Computer Science 2024-09-18 Zaiwei Chen , Siva Theja Maguluri , Martin Zubeldia