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Using, as main tool, the convergence theorem for discrete martingales and the mean value property of harmonic functions we solve, a particular case of, Dirichlet problem.

Probability · Mathematics 2010-10-29 José Villa

Training - the optimisation of complex models - is traditionally performed through small, local, iterative updates [D. E. Rumelhart, G. E. Hinton, R. J. Williams, Nature 323, 533-536 (1986)]. Approximating solutions through truncated…

Machine Learning · Computer Science 2025-10-08 Reza T. Batley , Sourav Saha

The Zygmund vector field maximal function conjecture is a long-standing open problem. This paper establishes a new boundedness criterion that significantly weakens the existing conditions in the literature. Specifically, the required decay…

Classical Analysis and ODEs · Mathematics 2026-05-26 Lingxiao Zhang

The micropolar Rayleigh-B{\'e}nard convection system, which consists of Navier-Stokes equations, the angular momentum equation, and the heat equation, is a strongly nonlinear, coupled, and saddle point structural multiphysics system. A…

Numerical Analysis · Mathematics 2025-12-03 Ming Cui , Akang Hou , Xiaoyu Dong

We study the asymptotic behavior of the least squares estimators of the unknown parameters of bifurcating autoregressive processes. Under very weak assumptions on the driven noise of the process, namely conditional pair-wise independence…

Probability · Mathematics 2009-06-29 Bernard Bercu , Benoite de Saporta , Anne Gegout-Petit

Let $G$ be a semimartingale, and $S$ its Snell envelope. Under the assumption that $G\in\mathcal{H}^1$, we show that the finite-variation part of $S$ is absolutely continuous with respect to the decreasing part of the finite-variation part…

Probability · Mathematics 2018-12-04 Saul D. Jacka , Dominykas Norgilas

Neural operators excel as deterministic surrogates, but inevitably collapse to the conditional mean when applied to stochastic PDEs, discarding the variance and tail structure upon which uncertainty quantification depends. Recovering this…

Machine Learning · Computer Science 2026-05-18 Kai Hidajat

We consider a manufacturer who manages the end-of-life phase and takes one of the three actions at each period: (1) place an order, (2) use existing inventory, (3) stop holding inventory and use an outside/alternative source. Two examples…

Optimization and Control · Mathematics 2021-10-26 Emin Ozyoruk , Nesim K. Erkip , Çağın Ararat

For the stochastic six-vertex model on the quadrant $\mathbb{Z}_{\geq0}\times\mathbb{Z}_{\geq0}$ with step initial conditions and a single second-class particle at the origin, we show almost sure convergence of the speed of the second-class…

Probability · Mathematics 2025-01-22 Hindy Drillick , Levi Haunschmid-Sibitz

We consider a class of semi-Markov processes (SMP) such that the embedded discrete time Markov chain may be non-homogeneous. The corresponding augmented processes are represented as semi-martingales using stochastic integral equation…

Probability · Mathematics 2022-07-14 Anindya Goswami , Subhamay Saha , Ravishankar Kapildev Yadav

{Consider a c\`adl\`ag local martingale $M$ with square brackets $[M]$. In this paper, we provide upper and lower bounds for expectations of the type ${\mathbb E} [M]^{q/2}_{\tau}$, for any stopping time $\tau$ and $q\ge 2$, in terms of…

Probability · Mathematics 2022-12-02 Saul Jacka , Ma. Elena Hérnandez-Hérnandez

In an M-type 2 Banach space, firstly we explore some properties of the set-valued stochastic integral associated with the stationary Poisson point process. By using the Hahn decomposition theorem and bounded linear functional, we obtain the…

Probability · Mathematics 2022-01-10 Jinping Zhang , Itaru Mitoma , Yoshiaki Okazaki

We use the martingale convergence method to get the weak convergence theorem on general functionals of partial sums of independent heavy-tailed random variables. The limiting process is the stochastic integral driven by $\alpha-$stable…

Statistics Theory · Mathematics 2014-11-18 Zhengyan Lin , Hanchao Wang

Consider the following stochastic differential equation (SDE) $$dX_t = b(t,X_{t-}) \, dt+ dL_t, \quad X_0 = x,$$ driven by a $d$-dimensional L\'evy process $(L_t)_{t \geq 0}$. We establish conditions on the L\'evy process and the drift…

Probability · Mathematics 2020-05-01 Franziska Kühn , René L. Schilling

We study the posterior contraction rates of a Bayesian method with Gaussian process priors in nonparametric regression and its plug-in property for differential operators. For a general class of kernels, we establish convergence rates of…

Statistics Theory · Mathematics 2020-12-01 Zejian Liu , Meng Li

In this paper we estimate the rest of the approximation of a stationary process by a martingale in terms of the projections of partial sums. Then, based on this estimate, we obtain almost sure approximation of partial sums by a martingale…

Probability · Mathematics 2011-05-05 Florence Merlevède , Costel Peligrad , Magda Peligrad

We consider a branching Brownian motion in $\mathbb{R}^d$. We prove that there exists a random subset $\Theta$ of $\mathbb{S}^{d-1}$ such that the limit of the derivative martingale exists simultaneously for all directions $\theta \in…

Probability · Mathematics 2020-11-20 Roman Stasiński , Julien Berestycki , Bastien Mallein

For a fixed right process $X$ we investigate those functions $u$ for which $u(X)$ is a quasimartingale. We prove that $u(X)$ is a quasimartingale if and only if $u$ is the dif- ference of two finite excessive functions. In particular, we…

Probability · Mathematics 2017-02-22 Lucian Beznea , Iulian Cîmpean

In this paper, we consider the discounted continuous-time Markov decision process (CTMDP) with a lower bounding function. In this model, the negative part of each cost rate is bounded by the drift function, say $w$, whereas the positive…

Optimization and Control · Mathematics 2016-12-05 Xin Guo , Alexey Piunovskiy , Yi Zhang

For a class of stochastic differential equations with reflection for which a certain ${\mathbb{L}}^p$ continuity condition holds with $p>1$, it is shown that any weak solution that is a strong Markov process can be decomposed into the sum…

Probability · Mathematics 2010-10-12 Weining Kang , Kavita Ramanan
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