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We prove precise rates of convergence for monotone approximation schemes of fractional and nonlocal Hamilton-Jacobi-Bellman (HJB) equations. We consider diffusion corrected difference-quadrature schemes from the literature and new…

Analysis of PDEs · Mathematics 2023-09-04 Indranil Chowdhury , Espen R. Jakobsen

Trigonometric polynomials are widely used for the approximation of a smooth function $f$ from a set of nonuniformly spaced samples $\{f(x_j)\}_{j=0}^{N-1}$. If the samples are perturbed by noise, controlling the smoothness of the…

Numerical Analysis · Mathematics 2025-10-20 Thomas Strohmer

In recent years many efforts have been devoted to finding bidiagonal factorizations of nonsingular totally positive matrices, since their accurate computation allows to numerically solve several important algebraic problems with great…

Numerical Analysis · Mathematics 2024-08-16 Yasmina Khiar , Esmeralda Mainar , Eduardo Royo-Amondarain , Beatriz Rubio

By combining a certain approximation property in the spatial domain, and weighted $\ell_2$-summability of the Hermite polynomial expansion coefficients in the parametric domain obtained in [M. Bachmayr, A. Cohen, R. DeVore and G.…

Numerical Analysis · Mathematics 2026-01-06 Dinh Dũng

The augmented Lagrangian (AL) method that solves convex optimization problems with linear constraints has drawn more attention recently in imaging applications due to its decomposable structure for composite cost functions and empirical…

Optimization and Control · Mathematics 2015-11-30 Hung Nien , Jeffrey A. Fessler

We adapt a symmetric interior penalty discontinuous Galerkin method using a patch reconstructed approximation space to solve elliptic eigenvalue problems, including both second and fourth order problems in 2D and 3D. It is a direct…

Numerical Analysis · Mathematics 2019-11-26 Ruo Li , Zhiyuan Sun , Fanyi Yang

We consider the general polynomial optimization problem $P: f^*=\min \{f(x)\,:\,x\in K\}$ where $K$ is a compact basic semi-algebraic set. We first show that the standard Lagrangian relaxation yields a lower bound as close as desired to the…

Optimization and Control · Mathematics 2012-10-18 Jean Lasserre

We analyze the multivariate generalization of Howgrave-Graham's algorithm for the approximate common divisor problem. In the m-variable case with modulus N and approximate common divisor of size N^beta, this improves the size of the error…

Number Theory · Mathematics 2012-03-15 Henry Cohn , Nadia Heninger

We are presenting a method for computing the Fourier coefficients of a given polynomial regression by using the trapezoidal rule for numerical integration. As function basis we use the orthogonal Legendre polynomials. The results are…

Numerical Analysis · Mathematics 2013-12-02 Demetris T. Christopoulos

In this paper, we derive rates of convergence in the high-dimensional central limit theorem for Polyak--Ruppert averaged iterates generated by entropy-regularized asynchronous Q-learning with linear function approximation and a polynomial…

Machine Learning · Statistics 2026-05-19 Artemy Rubtsov , Rahul Singh , Eric Moulines , Alexey Naumov , Sergey Samsonov

Tomography is the area of reconstructing objects from projections. Here we wish to reconstruct a set of cells in a two dimensional grid, given the number of cells in every row and column. The set is required to be an hv-convex polyomino,…

Data Structures and Algorithms · Computer Science 2007-05-23 Christoph Durr , Marek Chrobak

Error estimates are rigorously derived for a semi-discrete version of a conservative spectral method for approximating the space-homogeneous Fokker-Planck-Landau (FPL) equation associated to hard potentials. The analysis included shows that…

Numerical Analysis · Mathematics 2020-09-23 Clark A. Pennie , Irene M. Gamba

This paper provides an a~priori error analysis of a localized orthogonal decomposition method (LOD) for the numerical stochastic homogenization of a model random diffusion problem. If the uniformly elliptic and bounded random coefficient…

Numerical Analysis · Mathematics 2020-12-03 Julian Fischer , Dietmar Gallistl , Daniel Peterseim

An exact conservative remapping scheme requires overlaps between two meshes and a reconstruction scheme on the old cells (Lagrangian mesh). While the are intensive discussion on reconstruction schemes, there are relative sparse discussion…

Numerical Analysis · Mathematics 2016-05-31 Xihua Xu , Shengxin Zhu

This diploma thesis is concerned with functional decomposition $f = g \circ h$ of polynomials. First an algorithm is described which computes decompositions in polynomial time. This algorithm was originally proposed by Zippel (1991). A…

Commutative Algebra · Mathematics 2011-07-05 Raoul Blankertz

We construct an approximate renormalization for Hamiltonian systems with two degrees of freedom in order to study the break-up of invariant tori with arbitrary frequency. We derive the equation of the critical surface of the renormalization…

Chaotic Dynamics · Physics 2009-10-31 C. Chandre , P. Moussa

Often, polynomials or rational functions, orthogonal for a particular inner product are desired. In practical numerical algorithms these polynomials are not constructed, but instead the associated recurrence relations are computed.…

Numerical Analysis · Mathematics 2023-11-28 Marc Van Barel , Niel Van Buggenhout , Raf Vandebril

We show that the coefficients of the three-term recurrence relation for orthogonal polynomials with respect to a semi-classical extension of the Laguerre weight satisfy the fourth Painlev\'e equation when viewed as functions of one of the…

Classical Analysis and ODEs · Mathematics 2013-10-04 Galina Filipuk , Walter Van Assche , Lun Zhang

This work proposes and analyzes a fully discrete numerical scheme for solving the Landau-Lifshitz-Gilbert (LLG) equation, which achieves fourth-order spatial accuracy and third-order temporal accuracy.Spatially, fourth-order accuracy is…

Numerical Analysis · Mathematics 2025-10-30 Changjian Xie , Cheng Wang

We analyze the convergence behaviour of a recently proposed algorithm for regularized estimation called Dual Augmented Lagrangian (DAL). Our analysis is based on a new interpretation of DAL as a proximal minimization algorithm. We…

Machine Learning · Statistics 2011-06-07 Ryota Tomioka , Taiji Suzuki , Masashi Sugiyama