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This paper provides new uniform rate results for kernel estimators of absolutely regular stationary processes that are uniform in the bandwidth and in infinite-dimensional classes of dependent variables and regressors. Our results are…

Econometrics · Economics 2020-05-21 Juan Carlos Escanciano

In this paper, we give interior gradient and Hessian estimates for systems of semi-linear degenerate elliptic partial differential equations on bounded domains, using both tools of backward stochastic differential equations and…

Probability · Mathematics 2018-08-01 Jun Dai , Shanjian Tang , Bingjie Wu

We consider a least-squares variational kernel-based method for numerical solution of second order elliptic partial differential equations on a multi-dimensional domain. In this setting it is not assumed that the differential operator is…

Numerical Analysis · Mathematics 2021-10-26 Salar Seyednazari , Mehdi Tatari , Davoud Mirzaei

Solutions to nonlinear integro-differential systems are regular outside a negligible closed subset whose Hausdorff dimension can be explicitly bounded from above. This subset can be characterized using quantitative, universal energy…

Analysis of PDEs · Mathematics 2025-01-16 Cristiana De Filippis , Giuseppe Mingione , Simon Nowak

In this paper we develop a numerical scheme based on quadratures to approximate solutions of integro-differential equations involving convolution kernels, $\nu$, of diffusive type. In particular, we assume $\nu$ is symmetric and…

Numerical Analysis · Mathematics 2020-11-03 Loic Cappanera , Gabriela Jaramillo , Cory Ward

This paper is devoted to the study of some nonlinear parabolic equations with discontinuous diffusion intensities. Such problems appear naturally in physical and biological models. Our analysis is based on variational techniques and in…

Analysis of PDEs · Mathematics 2021-02-09 Dohyun Kwon , Alpár Richárd Mészáros

We are interested in the threshold phenomena for propagation in nonlocal diffusion equations with some compactly supported initial data. In the so-called bistable and ignition cases, we provide the first quantitative estimates for such…

Analysis of PDEs · Mathematics 2022-01-06 Matthieu Alfaro , Arnaud Ducrot , Hao Kang

We study quantum dynamical semigroups generated by noncommutative unbounded elliptic operators which can be written as Lindblad type unbounded generators. Under appropriate conditions, we first construct the minimal quantum dynamical…

Mathematical Physics · Physics 2009-11-11 C. Bahn , C. K. Ko , Y. M. Park

In this paper, we study solutions $u$ of parabolic systems in divergence form with zero Dirichlet boundary conditions in the upper-half cylinder $Q_1^+\subset \mathbb{R}^{n+1}$, where the coefficients are weighted by $x_n^\alpha$,…

Analysis of PDEs · Mathematics 2025-07-31 Hongjie Dong , Seongmin Jeon

We consider the kernel partial least squares algorithm for non-parametric regression with stationary dependent data. Probabilistic convergence rates of the kernel partial least squares estimator to the true regression function are…

Statistics Theory · Mathematics 2017-06-13 Marco Singer , Tatyana Krivobokova , Axel Munk

We study the existence of Feller semigroups arising in the theory of multidimensional diffusion processes. We study bounded perturbations of elliptic operators with boundary conditions containing an integral over the closure of the domain…

Analysis of PDEs · Mathematics 2014-05-05 Pavel Gurevich

We are concerned with fully nonlinear possibly degenerate elliptic partial differential equations (PDEs) with superlinear terms with respect to $Du$. We prove several comparison principles among viscosity solutions which may be unbounded…

Analysis of PDEs · Mathematics 2010-10-04 Shigeaki Koike , Olivier Ley

We study elliptic and parabolic systems in divergence form with degenerate or singular coefficients. Under the conormal boundary condition on the flat boundary, we establish boundary Schauder type estimates when the coefficients have…

Analysis of PDEs · Mathematics 2025-09-26 Hongjie Dong , Seongmin Jeon

The covariant technique for calculating the heat kernel asymptotic expansion for an elliptic differential second order operator is generalized to manifolds with boundary. The first boundary coefficients of the asymptotic expansion which are…

High Energy Physics - Theory · Physics 2008-11-26 Ivan G. Avramidi

The use of second order boundary kernels for distribution function estimation was recently addressed in the literature (C. Tenreiro, 2013, Boundary kernels for distribution function estimation, REVSTAT-Statistical Journal, 11, 169-190). In…

Statistics Theory · Mathematics 2015-02-05 Carlos Tenreiro

We obtain Calder\'on-Zygmund type estimates for parabolic equations with Orlicz growth, where nonlinearities involved in the equations may be discontinuous for the space and time variables. In addition, we consider parabolic systems with…

Analysis of PDEs · Mathematics 2021-08-25 Jehan Oh , Jihoon Ok

Modern Bayesian optimization and adaptive sampling methods increasingly rely on nonlinear parametric models, yet theoretical guarantees for such models under adaptive data collection remain limited. Existing analyses largely focus on…

Machine Learning · Statistics 2026-05-14 Rafael Oliveira

Using probabilistic methods, we establish a-priori estimates for two classes of quasilinear parabolic systems of partial differential equations (PDEs). We treat in particular the case of a nonlinearity which has quadratic growth in the…

Probability · Mathematics 2023-04-05 Joe Jackson

This paper develops a semi-parametric procedure for estimation of unconditional quantile partial effects using quantile regression coefficients. The estimator is based on an identification result showing that, for continuous covariates,…

Econometrics · Economics 2024-01-02 Javier Alejo , Antonio F. Galvao , Julian Martinez-Iriarte , Gabriel Montes-Rojas

Non-conservative uncertainty bounds are key for both assessing an estimation algorithm's accuracy and in view of downstream tasks, such as its deployment in safety-critical contexts. In this paper, we derive a tight, non-asymptotic…

Machine Learning · Computer Science 2026-01-16 Amon Lahr , Johannes Köhler , Anna Scampicchio , Melanie N. Zeilinger
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