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We aim to analyze the behaviour of a finite-time stochastic system, whose model is not available, in the context of more rare and harmful outcomes. Standard estimators are not effective in making predictions about such outcomes due to their…

Methodology · Statistics 2022-07-29 Evan Arsenault , Yuheng Wang , Margaret P. Chapman

In this paper, a weak type (1,1) bound criterion is established for singular integral operator with rough kernel. As some applications of this criterion, we prove some important operators with rough kernel in harmonic analysis, such as…

Classical Analysis and ODEs · Mathematics 2017-08-15 Yong Ding , Xudong Lai

The separate tasks of denoising, least squares expectation, and manifold learning can often be posed in a common setting of finding the conditional expectations arising from a product of two random variables. This paper focuses on this more…

Machine Learning · Statistics 2024-02-15 Suddhasattwa Das

Subgradient algorithms for training support vector machines have been quite successful for solving large-scale and online learning problems. However, they have been restricted to linear kernels and strongly convex formulations. This paper…

Machine Learning · Computer Science 2011-11-04 Sangkyun Lee , Stephen J. Wright

A common data analysis task is the reduced-rank regression problem: $$\min_{\textrm{rank-}k \ X} \|AX-B\|,$$ where $A \in \mathbb{R}^{n \times c}$ and $B \in \mathbb{R}^{n \times d}$ are given large matrices and $\|\cdot\|$ is some norm.…

Data Structures and Algorithms · Computer Science 2021-07-02 Praneeth Kacham , David P. Woodruff

Low-rank approximation of kernels is a fundamental mathematical problem with widespread algorithmic applications. Often the kernel is restricted to an algebraic variety, e.g., in problems involving sparse or low-rank data. We show that…

Machine Learning · Computer Science 2023-10-02 Jason M. Altschuler , Pablo A. Parrilo

This article studies sufficient conditions on families of approximating kernels which provide $N$--term approximation errors from an associated nonlinear approximation space which match the best known orders of $N$--term wavelet expansion.…

Functional Analysis · Mathematics 2019-03-15 Keaton Hamm , Jeff Ledford

Critical Sobolev-type inequality for a class of weighted Sobolev spaces on the entire space is established. We also investigate the existence of extremal function for the associated variational problem. As an application, we prove the…

Analysis of PDEs · Mathematics 2024-06-28 José Francisco de Oliveira , Jeferson Silva

We study approximation of multivariate functions from a separable Hilbert space in the randomized setting with the error measured in the weighted $L_2$ norm. We consider algorithms that use standard information $\Lambda^{\rm std}$…

Numerical Analysis · Mathematics 2021-01-12 Wanting Lu , Heping Wang

Many practical optimization problems lack strong convexity. Fortunately, recent studies have revealed that first-order algorithms also enjoy linear convergences under various weaker regularity conditions. While the relationship among…

Optimization and Control · Mathematics 2026-02-05 Feng-Yi Liao , Lijun Ding , Yang Zheng

Building upon recent work by the author, we prove that multivariate integration in the following subspace of the Wiener algebra over $[0,1)^d$ is strongly polynomially tractable: \[ F_d:=\left\{ f\in C([0,1)^d)\:\middle| \:…

Numerical Analysis · Mathematics 2023-06-05 Takashi Goda

Learning kernels in operators from data lies at the intersection of inverse problems and statistical learning, providing a powerful framework for capturing non-local dependencies in function spaces and high-dimensional settings. In contrast…

Statistics Theory · Mathematics 2025-06-24 Sichong Zhang , Xiong Wang , Fei Lu

We study the asymptotic behavior of kernel estimators of asymptotic variances (or long-run variances) for a class of adaptive Markov chains. The convergence is studied both in $L^p$ and almost surely. The results also apply to Markov chains…

Probability · Mathematics 2011-05-17 Yves F. Atchadé

Consider the generalized absolute value function defined by \[ a(t) = \vert t \vert t^{n-1}, \qquad t \in \mathbb{R}, n \in \mathbb{N}_{\geq 1}. \] Further, consider the $n$-th order divided difference function $a^{[n]}: \mathbb{R}^{n+1}…

Functional Analysis · Mathematics 2020-10-21 Martijn Caspers , Fedor Sukochev , Dmitriy Zanin

We continue the work of [Camano, Lackner, Monk, SIAM J. Math. Anal., Vol. 49, No. 6, pp. 4376-4401 (2017)] on electromagnetic Stekloff eigenvalues. The authors recognized that in general the eigenvalues due not correspond to the spectrum of…

Numerical Analysis · Mathematics 2019-09-09 Martin Halla

Local stochastic volatility refers to a popular model class in applied mathematical finance that allows for "calibration-on-the-fly", typically via a particle method, derived from a formal McKean-Vlasov equation. Well-posedness of this…

Probability · Mathematics 2025-06-13 Peter K. Friz , Benjamin Jourdain , Thomas Wagenhofer , Alexandre Zhou

The well-known Caputo fractional derivative and the corresponding Caputo fractional integral occur naturally in many equations that model physical phenomena under inhomogeneous media. The relationship between the two fractional terms can be…

Numerical Analysis · Mathematics 2020-01-23 Wesley Davis , Richard Noren

Let $\sigma:\boldsymbol{\Sigma}\to\boldsymbol{\Sigma}$ be the left shift acting on $ \boldsymbol{\Sigma} $, a one-sided Markov subshift on a countable alphabet. Our intention is to guarantee the existence of $\sigma$-invariant Borel…

Dynamical Systems · Mathematics 2010-03-30 Rodrigo Bissacot , Eduardo Garibaldi

We study the integration problem over the $s$-dimensional unit cube on four types of Banach spaces of integrands. First we consider Haar wavelet spaces, consisting of functions whose Haar wavelet coefficients exhibit a certain decay…

Numerical Analysis · Mathematics 2026-01-21 Michael Gnewuch , Josef Dick , Lev Markhasin , Winfried Sickel

In the design of efficient simulation algorithms, one is often beset with a poor choice of proposal distributions. Although the performance of a given simulation kernel can clarify a posteriori how adequate this kernel is for the problem at…

Statistics Theory · Mathematics 2010-10-11 R. Douc , A. Guillin , J. -M. Marin , C. P. Robert