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Related papers: A BDG inequality for stochastic Volterra integrals

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We consider the problems of the numerical solution of the Cauchy problem for an evolutionary equation with memory when the kernel of the integral term is a difference one. The computational implementation is associated with the need to work…

Numerical Analysis · Mathematics 2021-10-29 Petr N. Vabishchevich

We consider distributed stochastic variational inequalities (VIs) on unbounded domains with the problem data that is heterogeneous (non-IID) and distributed across many devices. We make a very general assumption on the computational network…

We consider multiple stochastic integrals with respect to c\`adl\`ag martingales, which approximate a cylindrical Wiener process. We define a chaos expansion, analogous to the case of multiple Wiener stochastic integrals, for these…

Probability · Mathematics 2023-07-26 Paolo Grazieschi , Konstantin Matetski , Hendrik Weber

We consider a discretization of Caputo derivatives resulted from deconvolving a scheme for the corresponding Volterra integral. Properties of this discretization, including signs of the coefficients, comparison principles, and stability of…

Numerical Analysis · Mathematics 2019-08-19 Lei Li , Jian-Guo Liu

We consider the Fredholm one-dimensional boundary-value problems in Sobolev spaces.We have obtained several important results about the indixes of functional operators, the criterion of their correct well-posedness, the criterion of the…

Classical Analysis and ODEs · Mathematics 2019-12-13 Olena Atlasiuk , Vladimir Mikhailets

In this paper, we generalize to Gaussian Volterra processes the existence and uniqueness of solutions for a class of non linear backward stochastic differential equations (BSDE) and we establish the relation between the non linear BSDE and…

Probability · Mathematics 2020-05-15 Habiba Knani

The Volterra integral equations of the first kind with piecewise smooth kernel are considered. Such equations appear in the theory of optimal control of the evolving systems. The existence theorems are proved. The method for constructing…

Optimization and Control · Mathematics 2011-11-28 Denis Sidorov

As an alternative to the well-known methods of "chaining" and "bracketing" that have been developed in the study of random fields, a new method, which is based on a {\em stochastic maximal inequality} derived by using the formula for…

Probability · Mathematics 2017-08-16 Yoichi Nishiyama

In this paper, we provide a comprehensive theoretical analysis of Stochastic Gradient Descent (SGD) and its momentum variants (Polyak Heavy-Ball and Nesterov) for tracking time-varying optima under strong convexity and smoothness. Our…

Machine Learning · Statistics 2026-05-20 Sharan Sahu , Cameron J. Hogan , Martin T. Wells

This paper is concerned with Merton's portfolio optimization problem in a Volterra stochastic environment described by a multivariate fake stationary Volterra--Heston model. Due to the non-Markovianity and non-semimartingality of the…

Optimization and Control · Mathematics 2026-05-08 Emmanuel Gnabeyeu

Under quasi-monotone assumptions for coefficients, we show one kind of comparison theorem for multi-dimensional\textbf{\}backward doubly stochastic differential equations on infinite horizon. An example is given as well.

Probability · Mathematics 2010-05-25 Liangquan Zhang , Yufeng Shi

We consider finite-volume approximations of Fokker-Planck equations on bounded convex domains in $\mathbb{R}^d$ and study the corresponding gradient flow structures. We reprove the convergence of the discrete to continuous Fokker-Planck…

Analysis of PDEs · Mathematics 2020-08-26 Dominik Forkert , Jan Maas , Lorenzo Portinale

Simple bounds are obtained for the integral $\int_0^x\mathrm{e}^{-\gamma t}t^\nu I_\nu(t)\,\mathrm{d}t$, $x>0$, $\nu>-1/2$, $0\leq\gamma<1$, together with a natural generalisation of this integral. In particular, we obtain an upper bound…

Classical Analysis and ODEs · Mathematics 2025-01-22 Robert E. Gaunt

We propose a novel approach in noncommutative probability, which can be regarded as an analogue of good-$\lambda$ inequalities from the classical case due to Burkholder and Gundy (Acta Math {\bf124}: 249-304,1970). This resolves a…

Operator Algebras · Mathematics 2024-08-20 Yong Jiao , Adam Osekowski , Lian Wu

We derive a stochastic Gronwall lemma with suprema over the paths in the upper bound of the assumed affine-linear growth assumption. This allows applications to It\^o processes with coefficients which depend on earlier time points such as…

Probability · Mathematics 2022-06-03 Martin Hutzenthaler , Tuan Anh Nguyen

Motivated by the potential connection between metric-affine gravity and linear Generalized Uncertainty Principle (GUP) in the phase space, we develop a covariant form of linear GUP and an associated modified Poincar\'e algebra, which…

General Relativity and Quantum Cosmology · Physics 2024-04-15 Ahmed Farag Ali , Aneta Wojnar

We introduce a local non-determinism condition for Volterra It\^{o} processes that captures smoothing properties of possibly degenerate noise. By combining the stochastic sewing lemma with one-step Euler approximations, we first prove the…

Probability · Mathematics 2026-03-26 Martin Friesen

Motivated by the work of Busse et al. [6] on turbulent convection in a rotating layer, we exploit the long-run behavior for stochastic Lotka-Volterra (LV) systems both in pull-back trajectory and in stationary measure. It is proved…

Dynamical Systems · Mathematics 2016-03-02 Lifeng Chen , Zhao Dong , Jifa Jiang , Lei Niu , Jianliang Zhai

The aim of this paper is to study, in the infinite dimensional framework, the existence and uniqueness for the solution of the following multivalued generalized backward stochastic differential equation, considered on a random, possibly…

Probability · Mathematics 2015-10-30 Lucian Maticiuc , Aurel Răşcanu

Uniform stability is a notion of algorithmic stability that bounds the worst case change in the model output by the algorithm when a single data point in the dataset is replaced. An influential work of Hardt et al. (2016) provides strong…

Machine Learning · Computer Science 2020-06-15 Raef Bassily , Vitaly Feldman , Cristóbal Guzmán , Kunal Talwar