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Measurement error is a pervasive issue which renders the results of an analysis unreliable. The measurement error literature contains numerous correction techniques, which can be broadly divided into those which aim to produce exactly…

Methodology · Statistics 2021-11-08 Dylan Spicker , Michael P Wallace , Grace Y Yi

In practice, there often exist unobserved variables, also termed hidden variables, associated with both the response and covariates. Existing works in the literature mostly focus on linear regression with hidden variables. However, when the…

Methodology · Statistics 2025-09-03 Inbeom Lee , Yang Ning

Empirical divergence maximization (EDM) refers to a recently proposed strategy for estimating f-divergences and likelihood ratio functions. This paper extends the idea to empirical vector quantization where one seeks to empirically derive…

Information Theory · Computer Science 2015-06-03 Michael A. Lexa

Online evaluation of machine learning models is typically conducted through A/B experiments. Sequential statistical tests are valuable tools for analysing these experiments, as they enable researchers to stop data collection early without…

Methodology · Statistics 2025-10-08 Alexey Kurennoy , Majed Dodin , Tural Gurbanov , Ana Peleteiro Ramallo

The aim of this paper is to provide new perspectives on the relative finite elements accuracy. Starting from a geometrical interpretation of the error estimate which can be deduced from Bramble-Hilbert lemma, we derive a probability law…

Numerical Analysis · Mathematics 2019-01-14 Joel Chaskalovic , Franck Assous

We describe an algorithm to find maximal exact matches (MEMs) among HiFi reads with homopolymer errors. The main novelty in our work is that we resort to run-length compression to help deal with errors. Our method receives as input a…

Data Structures and Algorithms · Computer Science 2022-09-01 Diego Díaz-Domínguez , Simon J. Puglisi , Leena Salmela

We put forward an adaptive alpha (Type I Error) that decreases as the information grows, for hypothesis tests in which nested linear models are compared. A less elaborate adaptation was already presented in \citet{PP2014} for comparing…

Methodology · Statistics 2021-01-06 D. Vélez , M. E. Pérez , L. R. Pericchi

Understanding algorithmic error accumulation in quantum simulation is crucial due to its fundamental significance and practical applications in simulating quantum many-body system dynamics. Conventional theories typically apply the triangle…

Quantum Physics · Physics 2024-11-11 Boyang Chen , Jue Xu , Qi Zhao , Xiao Yuan

The approximation ratio has become one of the dominant measures in mechanism design problems. In light of analysis of algorithms, we define the \emph{smoothed approximation ratio} to compare the performance of the optimal mechanism and a…

Computer Science and Game Theory · Computer Science 2017-06-23 Xiaotie Deng , Yansong Gao , Jie Zhang

We study semi Lagrangian approximation schemes for Hamilton Jacobi Bellman equations arising from finite horizon optimal control problems. Classical error estimates for these schemes include the term $\frac{1}{\Delta t}$ which leads to…

Optimization and Control · Mathematics 2026-02-18 Alessandro Alla , Filippo Mayer

Exposure measurement error is a ubiquitous but often overlooked challenge in causal inference with observational data. Existing methods accounting for exposure measurement error largely rely on restrictive parametric assumptions, while…

In an error estimation of finite element solutions to the Poisson equation, we usually impose the shape regularity assumption on the meshes to be used. In this paper, we show that even if the shape regularity condition is violated, the…

Numerical Analysis · Mathematics 2024-08-19 Kenta Kobayashi , Takuya Tsuchiya

Approximating a function $f(x)$ on $[-1,1]$ based on $N+1$ samples is a classical problem in numerical analysis. If the samples come with heteroskedastic noise depending on $x$ of variance $\sigma(x)^2$, an $O(N\log N)$ algorithm for this…

Numerical Analysis · Mathematics 2025-08-13 Yuji Nakatsukasa , Yifu Zhang

In this paper we propose a Bayesian answer to testing problems when the hypotheses are not well separated. The idea of the method is to study the posterior distribution of a discrepancy measure between the parameter and the model we want to…

Statistics Theory · Mathematics 2017-06-28 Jean-Bernard Salomond

While significant progress has been made in heterogeneous treatment effect (HTE) estimation, the evaluation of HTE estimators remains underdeveloped. In this article, we propose a robust evaluation framework based on relative error, which…

Machine Learning · Statistics 2025-10-21 Jiayi Guo , Haoxuan Li , Ye Tian , Peng Wu

Simulation-based verification algorithms can provide formal safety guarantees for nonlinear and hybrid systems. The previous algorithms rely on user provided model annotations called discrepancy function, which are crucial for computing…

Systems and Control · Computer Science 2015-02-09 Chuchu Fan , Sayan Mitra

We consider the problem of estimating the partition function $Z(\beta)=\sum_x \exp(-\beta(H(x))$ of a Gibbs distribution with a Hamilton $H(\cdot)$, or more precisely the logarithm of the ratio $q=\ln Z(0)/Z(\beta)$. It has been recently…

Data Structures and Algorithms · Computer Science 2017-12-29 Vladimir Kolmogorov

This short note reports a new derivation of the optimal order of the a priori error estimates for conforming virtual element methods (VEM) on 3D polyhedral meshes based on an error equation. The geometric assumptions, which are necessary…

Numerical Analysis · Mathematics 2018-10-03 Shuhao Cao , Long Chen , Frank Lin

We derive a residual-based $hp$-a posteriori error estimator for hybrid high-order (HHO) methods on simplicial meshes applied to the biharmonic problem posed on two- and three-dimensional polytopal Lipschitz domains. The a posteriori error…

Numerical Analysis · Mathematics 2026-02-09 Zhaonan Dong , Alexandre Ern , Tanvi Wadhawan

The Gap-Hamming distance problem is the promise problem of deciding if the Hamming distance $h$ between two strings of length $n$ is greater than $a$ or less than $b$, where the gap $g=|a-b|\geq 1$ and $a$ and $b$ could depend on $n$. In…

Computational Complexity · Computer Science 2017-05-30 Marcos Villagra
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