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Related papers: A Lower Bound on WAFOM

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Quasi-Monte Carlo sampling can attain far better accuracy than plain Monte Carlo sampling. However, with plain Monte Carlo sampling it is much easier to estimate the attained accuracy. This article describes methods old and new to quantify…

Numerical Analysis · Mathematics 2025-07-16 Art B. Owen

The notion off-ideals is recent and has been studied in the papers[1] [2], [5], [10], [11], [12], [13], [14] and [15]. In this paper, we have generalized the idea off-ideals to quasi f-ideals. This extended class of ideals is much bigger…

Commutative Algebra · Mathematics 2020-09-09 Hasan Mahmood , Fazal Ur Rehman , Thai Thanh Nguyen , Muhammad Ahsan Binyamin

In this paper, we analyze the error estimate of a wavelet frame based image restoration method from degraded and incomplete measurements. We present the error between the underlying original discrete image and the approximate solution which…

Analysis of PDEs · Mathematics 2022-08-23 Jian-Feng Cai , Jae Kyu Choi , Jianbin Yang

High dimensional integrals can be approximated well by quasi-Monte Carlo methods. However, determining the number of function values needed to obtain the desired accuracy is difficult without some upper bound on an appropriate semi-norm of…

Numerical Analysis · Mathematics 2017-06-27 Fred J. Hickernell , Lluís Antoni Jiménez Rugama , Da Li

In this paper, we consider an online optimization process, where the objective functions are not convex (nor concave) but instead belong to a broad class of continuous submodular functions. We first propose a variant of the Frank-Wolfe…

Machine Learning · Statistics 2018-02-19 Lin Chen , Hamed Hassani , Amin Karbasi

We provide an upper bound on the number of neurons required in a shallow neural network to approximate a continuous function on a compact set with a given accuracy. This method, inspired by a specific proof of the Stone-Weierstrass theorem,…

Machine Learning · Statistics 2025-10-09 Frantisek Hakl , Vit Fojtik

The classical approaches to numerically integrating a function $f$ are Monte Carlo (MC) and quasi-Monte Carlo (QMC) methods. MC methods use random samples to evaluate $f$ and have error $O(\sigma(f)/\sqrt{n})$, where $\sigma(f)$ is the…

Data Structures and Algorithms · Computer Science 2024-08-14 Nikhil Bansal , Haotian Jiang

In this paper we present some bounds of Hausdorff measures of objects definable in o-minimal structures: sets, fibers of maps, inverse images of curves of maps, etc. Moreover, we also give some explicit bounds for semi-algebraic or…

Differential Geometry · Mathematics 2012-04-27 Ta Le Loi , Phan Phien

Several analog-to-digital conversion methods for bandlimited signals used in applications, such as Sigma Delta quantization schemes, employ coarse quantization coupled with oversampling. The standard mathematical model for the error accrued…

Information Theory · Computer Science 2010-04-21 Felix Krahmer , Rachel Ward

Quasi-Monte Carlo (QMC) points are a substitute for plain Monte Carlo (MC) points that greatly improve integration accuracy under mild assumptions on the problem. Because QMC can give errors that are $o(1/n)$ as $n\to\infty$, changing even…

Numerical Analysis · Mathematics 2021-12-14 Art B. Owen

Some recent work on confidence intervals for randomized quasi-Monte Carlo (RQMC) sampling found a surprising result: ordinary Student $t$ 95% confidence intervals based on a modest number of replicates were seen to be very effective and…

Numerical Analysis · Mathematics 2025-03-26 Zexin Pan , Art B. Owen

We investigate the use of randomized quasi-Monte Carlo (RQMC) in walk on spheres algorithms to solve boundary value problems for functions with Dirichlet boundary conditions in $\mathbb{R}^d$. For harmonic functions with $d=2$, the…

Numerical Analysis · Mathematics 2026-05-12 Valerie N. P. Ho , Art B. Owen

In the Cellular Dynamical Mean Field Theory (CDMFT), a strongly correlated system is represented by a small cluster of correlated sites, coupled to an adjustable bath of uncorrelated sites simulating the cluster's environment; the…

Strongly Correlated Electrons · Physics 2010-07-30 David Senechal

Multivariate shortfall risk measures provide a principled framework for quantifying systemic risk and determining capital allocations prior to aggregation in interconnected financial systems. Despite their well established theoretical…

Computational Finance · Quantitative Finance 2026-03-09 Chiheb Ben Hammouda , Truong Ngoc Nguyen

We consider the efficient construction of polynomial lattice rules, which are special cases of so-called quasi-Monte Carlo (QMC) rules. These are of particular interest for the approximate computation of multivariate integrals where the…

Numerical Analysis · Mathematics 2020-08-21 Adrian Ebert , Peter Kritzer , Onyekachi Osisiogu , Tetiana Stepaniuk

The Fisher information matrix (FIM) plays an important role in the analysis of parameter inference and system design problems. In a number of cases, however, the statistical data distribution and its associated information matrix are either…

Statistics Theory · Mathematics 2016-11-24 Dave Zachariah , Petre Stoica

Continuing demands for increased compute efficiency and communication bandwidth have led to the development of novel interconnect technologies with the potential to outperform conventional electrical interconnects. With a plurality of…

Emerging Technologies · Computer Science 2016-12-09 Shuai Sun , Vikram K. Narayana , Armin Mehrabian , Tarek El-Ghazawi , Volker J. Sorger

Accurate and precise control of large quantum systems is paramount to achieve practical advantages on quantum devices. Therefore, benchmarking the hardware errors in quantum computers has drawn significant attention lately. Existing…

Quantum Physics · Physics 2023-01-18 Bharath Hebbe Madhusudhana

Let $f:[0,1]^d\to\mathbb{R}$ be a completely monotone integrand as defined by Aistleitner and Dick (2015) and let points $\boldsymbol{x}_0,\dots,\boldsymbol{x}_{n-1}\in[0,1]^d$ have a non-negative local discrepancy (NNLD) everywhere in…

Numerical Analysis · Mathematics 2026-01-13 Michael Gnewuch , Peter Kritzer , Art B. Owen , Zexin Pan

A high order wavelet integral collocation method (WICM) is developed for general nonlinear boundary value problems in physics. This method is established based on Coiflet approximation of multiple integrals of interval bounded functions…

Numerical Analysis · Mathematics 2017-04-26 Lei Zhang , Jizeng Wang , Xiaojing Liu , Youhe Zhou