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In this paper, a novel pre- and post-processing algorithm is presented that can double the convergence rate of finite element approximations for linear wave problems. In particular, it is shown that a $q$-step pre- and post-processing…

Numerical Analysis · Mathematics 2020-02-05 Sjoerd Geevers

Near isometric orthogonal embeddings to lower dimensions are a fundamental tool in data science and machine learning. In this paper, we present the construction of such embeddings that minimizes the maximum distortion for a given set of…

Machine Learning · Statistics 2017-12-15 Kshiteej Sheth , Dinesh Garg , Anirban Dasgupta

Finite element methods usually construct basis functions and quadrature rules for multidimensional domains via tensor products of one-dimensional counterparts. While straightforward, this approach results in integration spaces larger than…

Numerical Analysis · Mathematics 2026-01-09 Tomas Teijeiro , Pouria Behnoudfar , Jamie M. Taylor , David Pardo , Victor M. Calo

In this paper a new hp-adaptive strategy for elliptic problems based on refinement history is proposed, which chooses h-, p- or hp-refinement on individual elements according to a posteriori error estimate, as well as smoothness estimate of…

Numerical Analysis · Computer Science 2017-01-25 Hui Liu , Tao Cui , Wei Leng , Linbo Zhang

The spectral $p$-norm and nuclear $p$-norm of matrices and tensors appear in various applications albeit both are NP-hard to compute. The former sets a foundation of $\ell_p$-sphere constrained polynomial optimization problems and the…

Optimization and Control · Mathematics 2024-07-12 Jiewen Guan , Simai He , Bo Jiang , Zhening Li

We propose a model for recoverable robust optimization with commitment. Given a combinatorial optimization problem and uncertainty about elements that may fail, we ask for a robust solution that, after the failing elements are revealed, can…

Data Structures and Algorithms · Computer Science 2023-06-16 Felix Hommelsheim , Nicole Megow , Komal Muluk , Britta Peis

We consider the problem of minimal correction of the training set to make it consistent with monotonic constraints. This problem arises during analysis of data sets via techniques that require monotone data. We show that this problem is…

Machine Learning · Computer Science 2007-05-23 Rustem Takhanov

This thesis explores algorithmic applications and limitations of convex relaxation hierarchies for approximating some discrete and continuous optimization problems. - We show a dichotomy of approximability of constraint satisfaction…

Computational Complexity · Computer Science 2025-09-01 Mrinalkanti Ghosh

We initiate the study of the following natural geometric optimization problem. The input is a set of axis-aligned rectangles in the plane. The objective is to find a set of horizontal line segments of minimum total length so that every…

Computational Geometry · Computer Science 2018-06-11 Timothy M. Chan , Thomas C. van Dijk , Krzysztof Fleszar , Joachim Spoerhase , Alexander Wolff

In this paper we study the a posteriori bounds for a conforming piecewise linear finite element approximation of the Signorini problem. We prove new rigorous a posteriori estimates of residual type in $L^{p}$, for $p \in (4,\infty)$ in two…

Numerical Analysis · Mathematics 2024-04-02 Ben S. Ashby , Tristan Pryer

A finite element methodology for large classes of variational boundary value problems is defined which involves discretizing two linear operators: (1) the differential operator defining the spatial boundary value problem; and (2) a Riesz…

Numerical Analysis · Mathematics 2017-12-08 Brendan Keith , Socratis Petrides , Federico Fuentes , Leszek Demkowicz

We introduce a new minimisation principle for Poisson equation using two variables: the solution and the gradient of the solution. This principle allows us to use any conforming finite element spaces for both variables, where the finite…

Numerical Analysis · Mathematics 2015-09-07 Bishnu P. Lamichhane

We discuss the computational complexity of special cases of the 3-dimensional (axial) assignment problem where the elements are points in a Cartesian space and where the cost coefficients are the perimeters of the corresponding triangles…

Optimization and Control · Mathematics 2014-09-03 Ante Ćustić , Bettina Klinz , Gerhard J. Woeginger

For the finite element solution of Poisson's equation, a local a posteriori error estimation based on the Hypercircle method is proposed. Even for the solution of Poisson's equation without the $H^2$ regularity, this method can provide…

Numerical Analysis · Mathematics 2019-05-24 Taiga Nakano , Xuefeng Liu

We establish the existence of liftings into discrete subspaces of $\mathbf{H}(\mathrm{div})$ of piecewise polynomial data on locally refined simplicial partitions of polygonal/polyhedral domains. Our liftings are robust with respect to the…

Numerical Analysis · Mathematics 2025-01-29 Alexandre Ern , Iain Smears , Martin Vohralík

We develop two local energy methods for distributed parameter port-Hamiltonian (pH) systems on one-dimensional spatial domains. The methods are applied to derive a characterization of exponential stability directly in terms of the energy…

Optimization and Control · Mathematics 2025-12-01 Marco Roschkowski , Hannes Gernandt

Many problems in science and engineering can be rigorously recast into minimizing a suitable energy functional. We have been developing efficient and flexible solution strategies to tackle various minimization problems by employing finite…

Computational Engineering, Finance, and Science · Computer Science 2023-10-03 Miroslav Frost , Alexej Moskovka , Jan Valdman

In \cite{cheung2019optimally}, the authors presented two finite element methods for approximating second order boundary value problems on polytopial meshes with optimal accuracy without having to utilize curvilinear mappings. This was done…

Numerical Analysis · Mathematics 2023-01-11 James Cheung

We show, in one dimension, that an $hp$-Finite Element Method ($hp$-FEM) discretisation can be solved in optimal complexity because the discretisation has a special sparsity structure that ensures that the reverse Cholesky factorisation…

Numerical Analysis · Mathematics 2025-11-11 Kars Knook , Sheehan Olver , Ioannis P. A. Papadopoulos

We unify and extend the semigroup and the PDE approaches to stochastic maximal regularity of time-dependent semilinear parabolic problems with noise given by a cylindrical Brownian motion. We treat random coefficients that are only…

Analysis of PDEs · Mathematics 2019-02-12 Pierre Portal , Mark Veraar