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Related papers: Uniform approximation of continuous couplings

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Special approximation technique for analysis of different characteristics of states of multipartite infinite-dimensional quantum systems is proposed and applied to study of the relative entropy of entanglement and its regularisation. We…

Quantum Physics · Physics 2024-01-11 M. E. Shirokov

It is well-known that assumptions of monotonicity in size-bias couplings may be used to prove simple, yet powerful, Poisson approximation results. Here we show how these assumptions may be relaxed, establishing explicit Poisson…

Probability · Mathematics 2019-01-30 Fraser Daly , Oliver Johnson

The basic goal of quantization for probability distribution is to reduce the number of values, which is typically uncountable, describing a probability distribution to some finite set and thus approximation of a continuous probability…

Probability · Mathematics 2020-07-03 Mrinal Kanti Roychowdhury , Wasiela Salinas

This is an up-to-date introduction to, and overview of, marginal likelihood computation for model selection and hypothesis testing. Computing normalizing constants of probability models (or ratio of constants) is a fundamental issue in many…

Computation · Statistics 2023-02-13 Fernando Llorente , Luca Martino , David Delgado , Javier Lopez-Santiago

Variational weak-coupling perturbation theory yields converging approximations, uniformly in the coupling strength. This allows us to calculate directly the coefficients of `strong-coupling' expansions. For the anharmonic oscillator we…

Quantum Physics · Physics 2016-09-08 Wolfhard Janke , Hagen Kleinert

We study random points on the real line generated by the eigenvalues in unitary invariant random matrix ensembles or by more general repulsive particle systems. As the number of points tends to infinity, we prove convergence of the…

Probability · Mathematics 2015-11-11 Kristina Schubert , Martin Venker

In many empirical studies of a large two-sided matching market (such as in a college admissions problem), the researcher performs statistical inference under the assumption that they observe a random sample from a large matching market. In…

Econometrics · Economics 2024-04-02 Jacob Schwartz , Kyungchul Song

In this paper, we derive optimality conditions (Chebyshev approximation) for multivariate functions. The theory of Chebyshev (uniform) approximation for univariate functions is very elegant. The optimality conditions are based on the notion…

Optimization and Control · Mathematics 2015-10-22 Nadezda Sukhorukova , Julien Ugon , David Yost

We establish general conditions under which there exists uniform in time convergence between a stochastic process and its approximated system. These standardised conditions consist of a local in time estimate between the original and the…

Probability · Mathematics 2024-12-09 Katharina Schuh , Iain Souttar

We present and study approximate notions of dimensional and margin complexity, which correspond to the minimal dimension or norm of an embedding required to approximate, rather then exactly represent, a given hypothesis class. We show that…

Machine Learning · Computer Science 2020-03-10 Pritish Kamath , Omar Montasser , Nathan Srebro

We describe some new univariate spline quasi-interpolants on uniform partitions of bounded intervals. Then we give some applications to numerical analysis: integration, differentiation and approximation of zeros.

Numerical Analysis · Mathematics 2016-08-16 Paul Sablonnière

In this paper we consider the coupled task scheduling problem with exact delay times on a single machine with the objective of minimizing the total completion time of the jobs. We provide constant-factor approximation algorithms for several…

Optimization and Control · Mathematics 2024-05-03 David Fischer , Péter Györgyi

We establish a quantitative normal approximation result for sums of random variables with multilevel local dependencies. As a corollary, we obtain a quantitative normal approximation result for linear functionals of random fields which may…

Probability · Mathematics 2019-05-27 Julian Fischer

A univariate continuous function can always be decomposed as the sum of a non-increasing function and a non-decreasing one. Based on this property, we propose a non-parametric regression method that combines two spline-fitted monotone…

Methodology · Statistics 2024-04-11 Lijun Wang , Xiaodan Fan , Hongyu Zhao , Jun S. Liu

Sufficient conditions for synchronization of coupled Lienard-type oscillators are investigated via averaging technique. Coupling considered here is pairwise, unidirectional, and described by a nonlinear function (whose graph resides in the…

Dynamical Systems · Mathematics 2010-03-15 S. Emre Tuna

We propose an efficient algorithm for approximate computation of the profile maximum likelihood (PML), a variant of maximum likelihood maximizing the probability of observing a sufficient statistic rather than the empirical sample. The PML…

Machine Learning · Computer Science 2017-12-21 Dmitri S. Pavlichin , Jiantao Jiao , Tsachy Weissman

Computing the similarity between two probability distributions is a recurring theme across control. We introduce a unified family of distances between the probability distributions of two random variables that is based on the discrepancy…

Systems and Control · Electrical Eng. & Systems 2025-10-03 Alexandros E. Tzikas , Arec Jamgochian , Nazim Kemal Ure , Mykel J. Kochenderfer , Stephen P. Boyd

In multistage perfect matching problems we are given a sequence of graphs on the same vertex set and asked to find a sequence of perfect matchings, corresponding to the sequence of graphs, such that consecutive matchings are as similar as…

Data Structures and Algorithms · Computer Science 2021-05-11 Markus Chimani , Niklas Troost , Tilo Wiedera

Applications of the principle of reduction of couplings to the standard model and supersymmetric grand unified theories are reviewed. Phenomenological applications of renormalization group invariant sum rules for soft supersymmetry-breaking…

High Energy Physics - Phenomenology · Physics 2007-05-23 Jisuke Kubo

We study the sharp bounds of $\mathbb{E}[X_1\cdots X_d]$ when the univariate marginal distributions are known, but the dependence structure between them is unspecified. Maximizing products over non-negative variables is straightforward via…

Statistics Theory · Mathematics 2026-04-27 Christopher Blier-Wong , Jinghui Chen
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