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In this paper, we investigate the convergence rate in the vanishing viscosity limit for solutions to superquadratic Hamilton--Jacobi equations with state constraints. For every $p>2$, we establish the rate of convergence for nonnegative…

Analysis of PDEs · Mathematics 2026-03-10 Prerona Dutta , Khai T. Nguyen , Son N. T. Tu

This paper concerns the analysis of a multiscale method for wave propagation problems in microscopically nonhomogeneous media. A direct numerical approximation of such problems is prohibitively expensive as it requires resolving the…

Numerical Analysis · Mathematics 2017-02-20 Doghonay Arjmand , Olof Runborg

We present a fourth-order accurate finite volume method for the solution of ideal magnetohydrodynamics (MHD). The numerical method combines high-order quadrature rules in the solution of semi-discrete formulations of hyperbolic conservation…

Instrumentation and Methods for Astrophysics · Physics 2018-10-17 Kyle Gerard Felker , James Stone

Here, we study quantitative homogenization of first-order convex Hamilton-Jacobi equations with $(u/\varepsilon)$-periodic Hamiltonians which typically appear in dislocation dynamics. Firstly, we establish the optimal convergence rate by…

Analysis of PDEs · Mathematics 2025-07-02 Hiroyoshi Mitake , Panrui Ni , Hung V. Tran

A numerical analysis of upwind type schemes for the nonlinear nonlocal aggregation equation is provided. In this approach, the aggregation equation is interpreted as a conservative transport equation driven by a nonlocal nonlinear velocity…

Analysis of PDEs · Mathematics 2018-08-31 François Delarue , Frédéric Lagoutìère , Nicolas Vauchelet

We study the weakly stable hyperbolic boundary value problem with a large zero order oscillatory coefficient. This problem is related to linearized problems in the study of Mach stem and vortex sheets. We wish to establish a uniform energy…

Analysis of PDEs · Mathematics 2025-05-15 Alvis Zahl

In this work we construct a low-order nonconforming approximation method for linear elasticity problems supporting general meshes and valid in two and three space dimensions. The method is obtained by hacking the Hybrid High-Order method,…

Numerical Analysis · Mathematics 2019-06-26 Michele Botti , Daniele A. Di Pietro , Alessandra Guglielmana

In this paper, we analyze the convergence rate of the Jacobi-Proximal Alternating Direction Method of Multipliers (ADMM) initially introduced by Deng et al. for the block-structured optimization problem with linear constraint. The algorithm…

Optimization and Control · Mathematics 2025-12-08 Hyelin Choi , Woocheol Choi

In this paper, we study the fundamental open question of finding the optimal high-order algorithm for solving smooth convex minimization problems. Arjevani et al. (2019) established the lower bound $\Omega\left(\epsilon^{-2/(3p+1)}\right)$…

Optimization and Control · Mathematics 2022-05-20 Dmitry Kovalev , Alexander Gasnikov

In this paper, we study local convergence of high-order Tensor Methods for solving convex optimization problems with composite objective. We justify local superlinear convergence under the assumption of uniform convexity of the smooth…

Optimization and Control · Mathematics 2021-05-21 Nikita Doikov , Yurii Nesterov

This paper is devoted to numerical approximations for the wave equation with a multiscale character. Our approach is formulated in the framework of the Localized Orthogonal Decomposition (LOD) interpreted as a numerical homogenization with…

Numerical Analysis · Mathematics 2015-09-23 Assyr Abdulle , Patrick Henning

We present a higher order space-time unfitted finite element method for convection-diffusion problems on coupled (surface and bulk) domains. In that way, we combine a method suggested by Heimann, Lehrenfeld, Preu{\ss} (SIAM J. Sci. Comput.…

Numerical Analysis · Mathematics 2025-04-28 Fabian Heimann

We propose a high-order version of the augmented Lagrangian method for solving convex optimization problems with linear constraints, which achieves arbitrarily fast -- and even superlinear -- convergence rates. First, we analyze the…

Optimization and Control · Mathematics 2026-01-21 Young-Ju Lee , Jongho Park

In this paper we construct high order finite volume schemes on networks of hyperbolic conservation laws with coupling conditions involving ODEs. We consider two generalized Riemann solvers at the junction, one of Toro-Castro type and a…

Numerical Analysis · Mathematics 2016-11-23 Raul Borsche , Jochen Kall

Motivated by the fact that the gradient-based optimization algorithms can be studied from the perspective of limiting ordinary differential equations (ODEs), here we derive an ODE representation of the accelerated triple momentum (TM)…

Optimization and Control · Mathematics 2020-08-26 Boya Sun , Jemin George , Solmaz Kia

We study a second order BDF (Backward Differentiation Formula) scheme for the numerical approximation of parabolic HJB (Hamilton-Jacobi-Bellman) equations. The scheme under consideration is implicit, non-monotone, and second order accurate…

Numerical Analysis · Mathematics 2018-02-21 Olivier Bokanowski , Athena Picarelli , Christoph Reisinger

Policy iteration is a widely used technique to solve the Hamilton Jacobi Bellman (HJB) equation, which arises from nonlinear optimal feedback control theory. Its convergence analysis has attracted much attention in the unconstrained case.…

Optimization and Control · Mathematics 2020-05-19 Sudeep Kundu , Karl Kunisch

In this paper, we establish the convergence of solutions to the viscous Hamilton-Jacobi equation (with a Tonelli Hamiltonian): \[ \lambda u +H(x, du)=\varepsilon(\lambda)\Delta u,\quad \lambda>0 \] as $\lambda\rightarrow 0_+$, once the…

Analysis of PDEs · Mathematics 2025-09-23 Zibo Wang , Jianlu Zhang

Regularized risk minimization with the binary hinge loss and its variants lies at the heart of many machine learning problems. Bundle methods for regularized risk minimization (BMRM) and the closely related SVMStruct are considered the best…

Machine Learning · Computer Science 2009-09-09 Ankan Saha , Xinhua Zhang , S. V. N. Vishwanathan

We study the convergence rate of Bregman gradient methods for convex optimization in the space of measures on a $d$-dimensional manifold. Under basic regularity assumptions, we show that the suboptimality gap at iteration $k$ is in…

Optimization and Control · Mathematics 2023-03-15 Lénaïc Chizat