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We propose new methods to speed up convergence of the Alternating Direction Method of Multipliers (ADMM), a common optimization tool in the context of large scale and distributed learning. The proposed method accelerates the speed of…

Machine Learning · Computer Science 2016-04-05 Changkyu Song , Sejong Yoon , Vladimir Pavlovic

The alternating direction method of multipliers (ADMM) is a versatile tool for solving a wide range of constrained optimization problems, with differentiable or non-differentiable objective functions. Unfortunately, its performance is…

Machine Learning · Computer Science 2017-07-20 Zheng Xu , Mario A. T. Figueiredo , Tom Goldstein

We carry out a rigorous error analysis of the first-order semi-discrete (in time) consistent splitting scheme coupled with a generalized scalar auxiliary variable (GSAV) approach for the Navier-Stokes equations with no-slip boundary…

Numerical Analysis · Mathematics 2023-01-05 Xiaoli Li , Jie Shen

This paper studies the performance Newton's iteration applied with Anderson acceleration for solving the incompressible steady Navier-Stokes equations. We manifest that this method converges superlinearly with a good initial guess, and…

Numerical Analysis · Mathematics 2022-02-15 Mengying Xiao

A discontinuous Galerkin pressure correction numerical method for solving the incompressible Navier-Stokes equations is formulated and analyzed. We prove unconditional stability of the propose scheme. Convergence of the discrete velocity is…

Numerical Analysis · Mathematics 2021-09-24 Rami Masri , Chen Liu , Beatrice Riviere

We study the Stokes--Poisson--Boltzmann equations with Dirichlet and Navier boundary conditions. The system consists of the incompressible Stokes equations coupled with a nonlinear Poisson--Boltzmann equation through electrostatic forcing…

Numerical Analysis · Mathematics 2026-04-15 Ayush Agrawal , Aparna Bansal , D. N. Pandey

Recent works showed that pressure-robust modifications of mixed finite element methods for the Stokes equations outperform their standard versions in many cases. This is achieved by divergence-free reconstruction operators and results in…

Numerical Analysis · Mathematics 2017-12-06 P. L. Lederer , C. Merdon , J. Schöberl

This paper introduces an adaptive time splitting technique for the solution of stiff evolutionary PDEs that guarantees an effective error control of the simulation, independent of the fastest physical time scale for highly unsteady…

Numerical Analysis · Mathematics 2012-04-10 Stéphane Descombes , Max Duarte , Thierry Dumont , Violaine Louvet , Marc Massot

The Navier-Stokes motions in a box with periodic boundary conditions are considered. First the existence of global regular two-dimensional solutions is proved. The solutions are such that continuous with respect to time norms are controlled…

Analysis of PDEs · Mathematics 2016-06-16 Wojciech M. Zajaczkowski

We propose first-order pressure-correction scheme for the incompressible Navier-Stokes equations, incorporating the recently developed the Dynamically Regularized Lagrange Multiplier (DRLM) methods. The resulting algorithms are fully…

Numerical Analysis · Mathematics 2026-03-18 Yi Shen , Rihui Lan , Hua Wang

This paper describes an adaptive preconditioner for numerical continuation of incompressible Navier--Stokes flows. The preconditioner maps the identity (no preconditioner) to the Stokes preconditioner (preconditioning by Laplacian) through…

Numerical Analysis · Mathematics 2017-08-02 C. Beaume

We present a numerical scheme for approximating the incompressible Navier-Stokes equations based on an auxiliary variable associated with the total system energy. By introducing a dynamic equation for the auxiliary variable and…

Fluid Dynamics · Physics 2019-05-01 Lianlei Lin , Suchuan Dong

This paper introduces a parameter adaptation-based control law for a class of nonlinear, control-affine, safety-critical systems subject to additive, parameter-affine model uncertainty. It is shown that the uncertainty is learned in…

Optimization and Control · Mathematics 2023-08-02 Mitchell Black , Ehsan Arabi , Dimitra Panagou

The alternating direction method of multipliers (ADMM) has been widely adopted in low-rank approximation and low-order model identification tasks; however, the performance of nonconvex ADMM is highly reliant on the choice of penalty…

Optimization and Control · Mathematics 2023-09-11 Qingyuan Liu , Zhengchao Huang , Hao Ye , Dexian Huang , Chao Shang

For many algorithms, parameter tuning remains a challenging and critical task, which becomes tedious and infeasible in a multi-parameter setting. Multi-penalty regularization, successfully used for solving undetermined sparse regression of…

Machine Learning · Statistics 2017-10-12 Markus Grasmair , Timo Klock , Valeriya Naumova

In the report, we propose a family of variable time-stepping ensemble algorithms for solving multiple incompressible Navier-Stokes equations (NSE) at one pass. The one-leg, two-step methods designed by Dahlquist, Liniger, and Nevanlinna…

Numerical Analysis · Mathematics 2024-07-30 Wenlong Pei

First order optimization algorithms play a major role in large scale machine learning. A new class of methods, called adaptive algorithms, were recently introduced to adjust iteratively the learning rate for each coordinate. Despite great…

Machine Learning · Computer Science 2019-10-01 André Belotto da Silva , Maxime Gazeau

The goal of this paper is to introduce a simple finite element method to solve the Stokes and the Navier-Stokes equations. This method is in primal velocity-pressure formulation and is so simple such that both velocity and pressure are…

Numerical Analysis · Mathematics 2016-10-19 Lin Mu , Xiu Ye

We develop two unfitted finite element methods for the Stokes equations using $H^{\text{div}}$-conforming finite elements. Both methods achieve optimal convergence for velocity, ensure pointwise divergence-free velocity fields, and produce…

Numerical Analysis · Mathematics 2024-09-04 Thomas Frachon , Erik Nilsson , Sara Zahedi

We continue our work reported earlier (A. Muriel and M. Dresden, Physica D 101, 299, 1997) to calculate the time evolution of the one-particle distribution function. An improved operator formalism, heretofore unexplored, is used for uniform…

Mathematical Physics · Physics 2010-12-01 Amador Muriel