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The focus of this article is the approximation of functions which are analytic on a compact interval except at the endpoints. Typical numerical methods for approximating such functions depend upon the use of particular conformal maps from…

Numerical Analysis · Mathematics 2014-05-05 Ben Adcock , Mark Richardson

A simple version of exact finite dimensional reduction for the variational setting of mechanical systems is presented. It is worked out by means of a thorough global version of the implicit function theorem for monotone operators. Moreover,…

Mathematical Physics · Physics 2011-05-24 Franco Cardin , Giuseppe De Marco , Alessandro Sfondrini

In the presence of model risk, it is well-established to replace classical expected values by worst-case expectations over all models within a fixed radius from a given reference model. This is the "robustness" approach. We show that…

Risk Management · Quantitative Finance 2015-10-07 Thomas Kruse , Judith C. Schneider , Nikolaus Schweizer

This note provides new closed forms evaluations of a few classes of exponential sums associated with elliptic curves and hyperelliptic curves.

Number Theory · Mathematics 2011-03-23 N. A. Carella

We derive computable error estimates for finite element approximations of linear elliptic partial differential equations (PDE) with rough stochastic coefficients. In this setting, the exact solutions contain high frequency content that…

Numerical Analysis · Mathematics 2018-09-18 Eric Joseph Hall , Håkon Hoel , Mattias Sandberg , Anders Szepessy , Raúl Tempone

The theory of Chebyshev approximation has been extensively studied. In most cases, the optimality conditions are based on the notion of alternance or alternating sequence (that is, maximal deviation points with alternating deviation signs).…

Functional Analysis · Mathematics 2025-01-30 Nadezda Sukhorukova , Julien Ugon

The idea of slicing divergences has been proven to be successful when comparing two probability measures in various machine learning applications including generative modeling, and consists in computing the expected value of a `base…

Machine Learning · Statistics 2022-01-05 Kimia Nadjahi , Alain Durmus , Lénaïc Chizat , Soheil Kolouri , Shahin Shahrampour , Umut Şimşekli

We develop and analyze $M$-estimation methods for divergence functionals and the likelihood ratios of two probability distributions. Our method is based on a non-asymptotic variational characterization of $f$-divergences, which allows the…

Statistics Theory · Mathematics 2016-11-18 XuanLong Nguyen , Martin J. Wainwright , Michael I. Jordan

The distribution of the sum of r-th power of standard normal random variables is a generalization of the chi-squared distribution. In this paper, we represent the probability density function of the random variable by an one-dimensional…

Classical Analysis and ODEs · Mathematics 2018-06-25 Tamio Koyama

Measures of uncertainty and divergence are introduced for interval-valued probability distributions and are shown to have desirable mathematical properties. A maximum uncertainty inference procedure for marginal interval distributions is…

Artificial Intelligence · Computer Science 2013-04-08 Michael Pittarelli

Methodology is provided towards the solution of the minimum enclosing ball problem. This problem concerns the determination of the unique spherical surface of smallest radius enclosing a given bounded set in the d-dimensional Euclidean…

Computational Geometry · Computer Science 2024-10-16 Michael N. Vrahatis

We derive a new closed-form variance-adaptive confidence sequence (CS) for estimating the average conditional mean of a sequence of bounded random variables. Empirically, it yields the tightest closed-form CS we have found for tracking…

Statistics Theory · Mathematics 2025-12-25 Ben Chugg , Aaditya Ramdas

The bipartite matching problem is widely applied in the field of transportation; e.g., to find optimal matches between supply and demand over time and space. Recent efforts have been made on developing analytical formulas to estimate the…

Optimization and Control · Mathematics 2025-09-11 Yuhui Zhai , Shiyu Shen , Yanfeng Ouyang

In this work, we discuss the problem of approximating a multivariate function by discrete least squares projection onto a polynomial space using a specially designed deterministic point set. The independent variables of the function are…

Numerical Analysis · Mathematics 2014-01-07 Tao Zhou , Akil Narayan , Zhiqiang Xu

A generalization of expectiles for d-dimensional multivariate distribution functions is introduced. The resulting geometric expectiles are unique solutions to a convex risk minimization problem and are given by d-dimensional vectors. They…

Risk Management · Quantitative Finance 2018-01-19 Klaus Herrmann , Marius Hofert , Melina Mailhot

This paper concerns the construction and analysis of a numerical scheme for a mixed discrete-continuous fragmentation equation. A finite volume scheme is developed, based on a conservative formulation of a truncated version of the…

Numerical Analysis · Mathematics 2019-02-06 Graham Baird , Endre Süli

In this paper, we consider the explicit expressions of the normwise condition number for the scaled total least squares problem. Some techniques are introduced to simplify the expression of the condition number, and some new results are…

Numerical Analysis · Mathematics 2019-07-08 Shaoxin Wang , Hanyu Li , Hu Yang

We compute the expected value of Dirichlet $L$-functions defined over $\mathbb{F}_q[T]$ attached to cubic characters evaluated at an arbitrary $s \in (0,1)$. We find a transition term at the point $s=\frac{1}{3}$, reminiscent of the…

Number Theory · Mathematics 2025-02-10 Chantal David , Patrick Meisner

In optimal prediction methods one estimates the future behavior of underresolved systems by solving reduced systems of equations for expectations conditioned by partial data; renormalization group methods reduce the number of variables in…

Mathematical Physics · Physics 2007-05-23 Alexandre J. Chorin

We consider the approximation of a convolution of possibly different probability measures by (compound) Poisson distributions and also by related signed measures of higher order. We present new total variation bounds having a better…

Probability · Mathematics 2017-03-08 Bero Roos