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Central limit theorems are established for the sum, over a spatial region, of observations from a linear process on a $d$-dimensional lattice. This region need not be rectangular, but can be irregularly-shaped. Separate results are…

Statistics Theory · Mathematics 2016-01-07 S. N. Lahiri , Peter M. Robinson

We investigate stochastic averaging theory for locally Lipschitz discrete-time nonlinear systems with stochastic perturbation and its applications to convergence analysis of discrete-time stochastic extremum seeking algorithms. Firstly, by…

Optimization and Control · Mathematics 2015-02-18 Shu-Jun Liu , Miroslav Krstic

In the study of shapes of human organs using computational anatomy, variations are found to arise from inter-subject anatomical differences, disease-specific effects, and measurement noise. This paper introduces a stochastic model for…

Computer Vision and Pattern Recognition · Computer Science 2016-12-19 Alexis Arnaudon , Darryl D. Holm , Akshay Pai , Stefan Sommer

We study the optimal control of path-dependent piecewise deterministic processes. An appropriate dynamic programming principle is established. We prove that the associated value function is the unique minimax solution of the corresponding…

Probability · Mathematics 2025-10-28 Elena Bandini , Christian Keller

We consider estimating a low-dimensional parameter in an estimating equation involving high-dimensional nuisances that depend on the parameter. A central example is the efficient estimating equation for the (local) quantile treatment effect…

Machine Learning · Statistics 2022-08-18 Nathan Kallus , Xiaojie Mao , Masatoshi Uehara

The local volatility model is a widely used for pricing and hedging financial derivatives. While its main appeal is its capability of reproducing any given surface of observed option prices---it provides a perfect fit---the essential…

Computational Finance · Quantitative Finance 2019-01-24 Martin Tegnér , Stephen Roberts

In this work, we present the convergence analysis of one-point large deviations rate functions (LDRFs) of the spatial finite difference method (FDM) for stochastic wave equations with small noise, which is essentially about the asymptotical…

Numerical Analysis · Mathematics 2022-09-20 Diancong Jin , Jialin Hong , Derui Sheng

This paper provides a unifying theoretical framework for stochastic optimization algorithms by means of a latent stochastic variational problem. Using techniques from stochastic control, the solution to the variational problem is shown to…

Machine Learning · Computer Science 2019-10-29 Philippe Casgrain

Locally interpretable model agnostic explanations (LIME) method is one of the most popular methods used to explain black-box models at a per example level. Although many variants have been proposed, few provide a simple way to produce high…

Machine Learning · Computer Science 2023-10-04 Amit Dhurandhar , Karthikeyan Ramamurthy , Kartik Ahuja , Vijay Arya

A local projection model is defined by a set of linear regressions that account for the associations between exogenous variables and an endogenous variable observed at different time points. While it is standard practice to separately…

Methodology · Statistics 2020-07-14 Masahiro Tanaka

In this paper, we develop Stein's method for binomial approximation using the stop-loss metric that allows one to obtain a bound on the error term between the expectation of call functions. We obtain the results for a locally dependent…

Probability · Mathematics 2022-03-25 Amit N. Kumar , P. Vellaisamy

In this paper, we investigate the precise local large deviation probabilities for random sums of independent real-valued random variables with a common distribution $F$, where $F(x+\Delta)=F((x, x+T])$ is an $\mathcal{O}$-regularly varying…

Probability · Mathematics 2016-07-05 Qiuying Zhang , Fengyang Cheng

Parameter estimation for non-stationary stochastic differential equations (SDE) with an arbitrary nonlinear drift, and nonlinear diffusion is accomplished in combination with a non-parametric clustering methodology. Such a model-based…

Optimization and Control · Mathematics 2021-09-07 Vyacheslav Boyko , Sebastian Krumscheid , Nikki Vercauteren

We study the asymptotic behaviour of stationary densities of one-dimensional random diffeomorphisms, at the boundaries of their support, which correspond to deterministic fixed points of extremal diffeomorphisms. In particular, we show how…

Probability · Mathematics 2024-10-25 Jeroen S. W. Lamb , Guillermo Olicón-Méndez , Martin Rasmussen

We study the dynamic regret of multi-armed bandit and experts problem in non-stationary stochastic environments. We introduce a new parameter $\Lambda$, which measures the total statistical variance of the loss distributions over $T$ rounds…

Machine Learning · Computer Science 2019-06-24 Chen-Yu Wei , Yi-Te Hong , Chi-Jen Lu

We consider the inverse problem of recovering stationary coefficients in a class of dynamical Schr\"odinger equations with locally analytic nonlinear terms. Upon treating the well-posedness for small initial data and trivial boundary data,…

Analysis of PDEs · Mathematics 2025-08-28 Pranav Arrepu , Hanming Zhou

In this paper we mainly investigate the strong and weak well-posedness of a class of McKean-Vlasov stochastic (partial) differential equations. The main existence and uniqueness results state that we only need to impose some local…

Probability · Mathematics 2024-01-15 Wei Hong , Shanshan Hu , Wei Liu

We conduct an extensive study of nonlinear localized modes (NLMs), which are temporally periodic and spatially localized structures, in a two-dimensional array of repelling magnets. In our experiments, we arrange a lattice in a hexagonal…

This paper is concerned with a general non-homogeneous stochastic linear quadratic (LQ) control problem with regime switching and random coefficients. We obtain the explicit optimal state feedback control and optimal value for this problem…

Optimization and Control · Mathematics 2023-07-17 Ying Hu , Xiaomin Shi , Zuo Quan Xu

This paper is devoted to proving the strong averaging principle for slow-fast stochastic partial differential equations with locally monotone coefficients, where the slow component is a stochastic partial differential equations with locally…

Probability · Mathematics 2019-09-11 Wei Liu , Michael Röckner , Xiaobin Sun , Yingchao Xie