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In this paper we propose a multiscale method for the acoustic wave equation in highly oscillatory media. We use a higher-order extension of the localized orthogonal decomposition method combined with a higher-order time stepping scheme and…

Numerical Analysis · Mathematics 2024-07-23 Felix Krumbiegel , Roland Maier

Quasi-Monte Carlo (QMC) quadrature rules using higher order digital nets and sequences have been shown to achieve the almost optimal rate of convergence of the worst-case error in Sobolev spaces of arbitrary fixed smoothness $\alpha\in…

Numerical Analysis · Mathematics 2019-12-09 Takashi Goda , Kosuke Suzuki , Takehito Yoshiki

A crucial part of successful wave propagation related inverse problems is an efficient and accurate numerical scheme for solving the seismic wave equations. In particular, the numerical solution to a multi-dimensional Helmholtz equation can…

Numerical Analysis · Mathematics 2021-03-11 Hatef Dastour , Wenyuan Liao

We establish or refute the optimality of inexact second-order methods for unconstrained nonconvex optimization from the point of view of worst-case evaluation complexity, improving and generalizing the results of Cartis, Gould and Toint…

Optimization and Control · Mathematics 2021-05-31 Coralia Cartis , Nick I. M. Gould , Philippe L. Toint

We study the half-plane problem for the elastic wave equation subject to a free surface boundary condition, with particular emphasis on almost incompressible materials. A normal mode analysis is developed to estimate the solution in terms…

Numerical Analysis · Mathematics 2011-05-04 Heinz-Otto Kreiss , N. Anders Petersson

This work presents a numerical study of the Dirichlet problem for the fractional Laplacian $(-\Delta)^s$ with $s\in(0,1)$ using Finite Element methods with non-standard bases. Classical approaches based on piece-wise linear basis yield…

Numerical Analysis · Mathematics 2025-11-19 Félix del Teso , Stefano Fronzoni , David Gómez-Castro

The study of first-order optimization algorithms (FOA) typically starts with assumptions on the objective functions, most commonly smoothness and strong convexity. These metrics are used to tune the hyperparameters of FOA. We introduce a…

Machine Learning · Computer Science 2024-05-30 Charles Guille-Escuret , Baptiste Goujaud , Manuela Girotti , Ioannis Mitliagkas

Smooth finite-sum optimization has been widely studied in both convex and nonconvex settings. However, existing lower bounds for finite-sum optimization are mostly limited to the setting where each component function is (strongly) convex,…

Optimization and Control · Mathematics 2019-02-01 Dongruo Zhou , Quanquan Gu

In this paper, based on the developed nonlinear fourth-order operator and method of order reduction, a novel fourth-order compact difference scheme is constructed for the mixed-type time-fractional Burgers' equation, from which…

Numerical Analysis · Mathematics 2022-09-02 Xiangyi Peng , Da Xu , Wenlin Qiu

We introduce new adaptive schemes for the one- and two-dimensional hyperbolic systems of conservation laws. Our schemes are based on an adaption strategy recently introduced in [{\sc S. Chu, A. Kurganov, and I. Menshov}, Appl. Numer. Math.,…

Numerical Analysis · Mathematics 2026-04-10 Shaoshuai Chu , Pingyao Feng , Vadim A. Kolotilov , Alexander Kurganov , Vladimir V. Ostapenko

A unified framework for fourth-order semilinear problems with trilinear nonlinearity and general source allows for quasi-best approximation with lowest-order finite element methods. This paper establishes the stability and a priori error…

Numerical Analysis · Mathematics 2023-05-23 Carsten Carstensen , Neela Nataraj , Gopikrishnan C. Remesan , Devika Shylaja

Suppose that a solution $\widetilde{\mathbf{x}}$ to an underdetermined linear system $\mathbf{b} = \mathbf{A} \mathbf{x}$ is given. $\widetilde{\mathbf{x}}$ is approximately sparse meaning that it has a few large components compared to…

Information Theory · Computer Science 2015-06-29 Mohammadreza Malek-Mohammadi , Cristian R. Rojas , Magnus Jansson , Massoud Babaie-Zadeh

During recent years the interest of optimization and machine learning communities in high-probability convergence of stochastic optimization methods has been growing. One of the main reasons for this is that high-probability complexity…

In this paper, we first prove the weak intermittency, and in particular the sharp exponential order $C\lambda^4t$ of the second moment of the exact solution of the stochastic heat equation with multiplicative noise and periodic boundary…

Numerical Analysis · Mathematics 2021-03-04 Chuchu Chen , Tonghe Dang , Jialin Hong

The problem of learning threshold functions is a fundamental one in machine learning. Classical learning theory implies sample complexity of $O(\xi^{-1} \log(1/\beta))$ (for generalization error $\xi$ with confidence $1-\beta$). The private…

Machine Learning · Computer Science 2022-11-14 Edith Cohen , Xin Lyu , Jelani Nelson , Tamás Sarlós , Uri Stemmer

We present and compare third- as well as fifth-order accurate finite difference schemes for the numerical solution of the compressible ideal MHD equations in multiple spatial dimensions. The selected methods lean on four different…

High Energy Astrophysical Phenomena · Physics 2015-05-18 A. Mignone , P. Tzeferacos , G. Bodo

In this paper, we propose a new method based on the Sliding Algorithm from Lan(2016, 2019) for the convex composite optimization problem that includes two terms: smooth one and non-smooth one. Our method uses the stochastic noised…

Optimization and Control · Mathematics 2021-06-16 Aleksandr Beznosikov , Eduard Gorbunov , Alexander Gasnikov

We consider the first-order system space-time formulation of the heat equation introduced in [Bochev, Gunzburger, Springer, New York (2009)], and analyzed in [F\"uhrer, Karkulik, Comput. Math. Appl. 92 (2021)] and [Gantner, Stevenson, ESAIM…

Numerical Analysis · Mathematics 2024-03-01 Gregor Gantner , Rob Stevenson

We consider initial-boundary problems for general linear first-order strictly hyperbolic systems with local or nonlocal nonlinear boundary conditions. While boundary data are supposed to be smooth, initial conditions can contain…

Analysis of PDEs · Mathematics 2025-12-10 Irina Kmit

We design an algorithm which finds an $\epsilon$-approximate stationary point (with $\|\nabla F(x)\|\le \epsilon$) using $O(\epsilon^{-3})$ stochastic gradient and Hessian-vector products, matching guarantees that were previously available…

Machine Learning · Computer Science 2020-06-25 Yossi Arjevani , Yair Carmon , John C. Duchi , Dylan J. Foster , Ayush Sekhari , Karthik Sridharan