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This paper introduces a new strategy for setting the regularization parameter when solving large-scale discrete ill-posed linear problems by means of the Arnoldi-Tikhonov method. This new rule is essentially based on the discrepancy…

Numerical Analysis · Mathematics 2013-07-02 Silvia Gazzola , Paolo Novati , Maria Rosaria Russo

Estimators of parameters of truncated distributions, namely the truncated normal distribution, have been widely studied for a known truncation region. There is also literature for estimating the unknown bounds for known parent…

Computation · Statistics 2026-01-16 Dylan Borchert , Semhar Michael , Christopher Saunders

Solving the generalized eigenvalue problem is a useful method for finding energy eigenstates of large quantum systems. It uses projection onto a set of basis states which are typically not orthogonal. One needs to invert a matrix whose…

Nuclear Theory · Physics 2023-04-05 Caleb Hicks , Dean Lee

In this article, we show that the projection-free, snapshot-based, balanced truncation method can be applied directly to unstable systems. We prove that even for unstable systems, the unmodified balanced proper orthogonal decomposition…

Fluid Dynamics · Physics 2015-08-27 Thibault L. B. Flinois , Aimee S. Morgans , Peter J. Schmid

We analyze a structure-preserving model order reduction technique for delay and stochastic delay equations based on the balanced truncation method and provide a system theoretic interpretation. Transferring error bounds based on Hankel…

Optimization and Control · Mathematics 2020-08-28 Simon Becker , Lorenz Richter

Effective operators have been used extensively to understand small deviations from the Standard Model in the search for new physics. So far there has been no general method to fit for small parameters when higher order corrections in these…

Data Analysis, Statistics and Probability · Physics 2017-05-25 Laure Berthier , Jeppe Trøst Nielsen

Given a stream of Bernoulli random variables, consider the problem of estimating the mean of the random variable within a specified relative error with a specified probability of failure. Until now, the Gamma Bernoulli Approximation Scheme…

Machine Learning · Computer Science 2022-10-25 Mark Huber

We derive normal approximation results for a class of stabilizing functionals of binomial or Poisson point process, that are not necessarily expressible as sums of certain score functions. Our approach is based on a flexible notion of the…

Probability · Mathematics 2022-10-20 Zhaoyang Shi , Krishnakumar Balasubramanian , Wolfgang Polonik

We develop a generalized gradient expansion of the inhomogeneous dynamical mean-field theory method for determining properties of ultracold atoms in a trap. This approach goes beyond the well-known local density approximation and at higher…

Quantum Gases · Physics 2016-08-17 J. K. Freericks , Shuyang Han , Karlis Mikelsons , H. R. Krishnamurthy

The simplest, and most common, stochastic model for population processes, including those from biochemistry and cell biology, are continuous time Markov chains. Simulation of such models is often relatively straightforward as there are…

Probability · Mathematics 2012-03-01 David F. Anderson , Masanori Koyama

Equilibrium or stationary solutions usually proceed through the exact balance between hyperbolic transport terms and source terms. Such equilibrium solutions are affected by truncation errors that prevent any classical numerical scheme from…

Numerical Analysis · Mathematics 2018-08-22 Maria Han Veiga , David A. Romero Velasco , Rémi Abgrall , Romain Teyssier

We introduce an algorithm based on a method of snapshots for computing approximate balanced truncations for discrete-time, stable, linear time-periodic systems. By construction, this algorithm is applicable to very high-dimensional systems,…

Optimization and Control · Mathematics 2007-08-06 Zhanhua Ma , Clarence W. Rowley , Gilead Tadmor

We propose new linear combinations of compositions of a basic second-order scheme with appropriately chosen coefficients to construct higher order numerical integrators for differential equations. They can be considered as a generalization…

Numerical Analysis · Mathematics 2024-04-25 Sergio Blanes , Fernando Casas , Luke Shaw

In this paper, the method of gaps, a technique for deriving closed-form expressions in terms of information measures for the generalization error of supervised machine learning algorithms is introduced. The method relies on the notion of…

Machine Learning · Computer Science 2026-01-01 Samir M. Perlaza , Xinying Zou

We study the problem of estimating the parameters of a Gaussian distribution when samples are only shown if they fall in some (unknown) subset $S \subseteq \R^d$. This core problem in truncated statistics has long history going back to…

Statistics Theory · Mathematics 2019-08-06 Vasilis Kontonis , Christos Tzamos , Manolis Zampetakis

We study a linearly transformed particle method for the aggregation equation with smooth or singular interaction forces. For the smooth interaction forces, we provide convergence estimates in $L^1$ and $L^\infty$ norms depending on the…

Numerical Analysis · Mathematics 2015-07-28 Martin Campos Pinto , José A. Carrillo , Frédérique Charles , Young-Pil Choi

In the article we propose a general scheme for solutions of some approximation problems under a rather general setting. We illustrate the application of the proposed scheme by a series of examples, in particular we show that many results in…

Functional Analysis · Mathematics 2023-12-29 Oleg Kovalenko

When averages of different experimental determinations of the same quantity are computed, each with statistical and systematic error components, then frequently the statistical and systematic components of the combined error are quoted…

Data Analysis, Statistics and Probability · Physics 2015-10-28 Jens Erler

A broader definition of generalized truncations of graphs is introduced followed by an exploration of some standard concepts and parameters with regard to generalized truncations.

Combinatorics · Mathematics 2020-07-10 Brian Alspach , Joshua B. Connor

We revisit the problem of estimating the parameters of a partially observed diffusion process, consisting of a hidden state process and an observed process, with a continuous time parameter. The estimation is to be done online, i.e. the…

Optimization and Control · Mathematics 2018-10-16 Simone Carlo Surace , Jean-Pascal Pfister