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Recently a useful finite-difference scheme was proposed in [Phys. Rev. E 98, 033302 (2018)] to solve Fokker-Planck equations with drift-admitting jumps. However, while the scheme is fifth order for the case with smooth drifts, it is only…

Statistical Mechanics · Physics 2019-11-05 Yaming Chen , Xiaogang Deng

Contemporary deep clustering approaches often rely on either contrastive or non-contrastive techniques to acquire effective representations for clustering tasks. Contrastive methods leverage negative pairs to achieve homogenous…

Machine Learning · Computer Science 2023-11-03 Abhishek Kumar , Dong-Gyu Lee

In this paper, we present a distributed model predictive control (DMPC) scheme for dynamically decoupled systems which are subject to state constraints, coupling state constraints and input constraints. In the proposed control scheme,…

Systems and Control · Electrical Eng. & Systems 2024-08-17 Adrian Wiltz , Fei Chen , Dimos V. Dimarogonas

Ordinary differential equations (ODEs) provide a powerful framework for modeling dynamic systems arising in a wide range of scientific domains. However, most existing ODE methods focus on a single system, and do not adequately address the…

Methodology · Statistics 2026-04-08 Shuoxun Xu , Zijian Guo , Brooke R. Staveland , Robert T. Knight , Lexin Li

Steady state simulations} of magnetized electron fluid equations with strong anisotropic diffusion based on the first-order hyperbolic approach is carried out using cell-centered higher order upwind schemes, linear and weighted essentially…

Computational Physics · Physics 2019-03-14 Amareshwara Sainadh Chamarthi , Kimiya Komurasaki , Rei Kawashima

We describe a fourth-order accurate finite-difference time-domain scheme for solving dispersive Maxwell's equations with nonlinear multi-level carrier kinetics models. The scheme is based on an efficient single-step three time-level…

Deploying Convolutional Neural Networks (CNNs) on resource-constrained devices necessitates efficient management of computational resources, often via distributed environments susceptible to latency from straggler nodes. This paper…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-09-09 Shuo Tan , Rui Liu , Xuesong Han , XianLei Long , Kai Wan , Linqi Song , Yong Li

In this work, we study advection-robust Hybrid High-Order discretizations of the Oseen equations. For a given integer $k\ge 0$, the discrete velocity unknowns are vector-valued polynomials of total degree $\le k$ on mesh elements and faces,…

Numerical Analysis · Mathematics 2018-02-20 Joubine Aghili , Daniele A. Di Pietro

In this paper, two kinds of high-order compact finite difference schemes for second-order derivative are developed. Then a second-order numerical scheme for Riemann-Liouvile derivative is established based on fractional center difference…

Numerical Analysis · Mathematics 2016-11-22 Hengfei Ding , Changpin Li

In this paper, a class of finite difference numerical techniques is presented to solve the second-order linear inhomogeneous damped wave equation. The consistency, stability, and convergences of these numerical schemes are discussed. The…

Numerical Analysis · Mathematics 2021-12-23 Fazel Hadadifard , Satbir Malhi , Zhengyi Xiao

In this article, we propose finite volume schemes for the $abcd$-systems and we establish stability and error estimates. The order of accuracy depends on the so-called BBM-type dispersion coefficients $b$ and $d$. If $bd>0$, the numerical…

Numerical Analysis · Mathematics 2018-10-31 Cosmin Burtea , Clémentine Courtès

Network consensus optimization has received increasing attention in recent years and has found important applications in many scientific and engineering fields. To solve network consensus optimization problems, one of the most well-known…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-09-10 Xin Zhang , Jia Liu , Zhengyuan Zhu , Elizabeth S. Bentley

It is shown how various ideas that are well established for the solution of Poisson's equation using plane wave and multigrid methods can be combined with wavelet concepts. The combination of wavelet concepts and multigrid techniques turns…

Computational Physics · Physics 2007-05-23 S. Goedecker

We present an adaptive-order positivity-preserving conservative finite-difference scheme that allows a high-order solution away from shocks and discontinuities while guaranteeing positivity and robustness at discontinuities. This is…

We propose a new numerical scheme of evolution for the Einstein equations using the discrete variational derivative method (DVDM). We derive the discrete evolution equation of the constraint using this scheme and show the constraint…

General Relativity and Quantum Cosmology · Physics 2017-10-24 Takuya Tsuchiya , Gen Yoneda

We present the hybridization of flux reconstruction methods for advection-diffusion problems. Hybridization introduces a new variable into the problem so that it can be reduced via static condensation. This allows the solution of implicit…

Numerical Analysis · Mathematics 2023-10-25 Carlos A. Pereira , Brian C. Vermeire

Randomized coordinate descent (RCD) is a popular optimization algorithm with wide applications in solving various machine learning problems, which motivates a lot of theoretical analysis on its convergence behavior. As a comparison, there…

Machine Learning · Computer Science 2021-08-18 Puyu Wang , Liang Wu , Yunwen Lei

Pseudospectral collocation methods and finite difference methods have been used for approximating an important family of soliton like solutions of the mKdV equation. These solutions present a structural instability which make difficult to…

Numerical Analysis · Mathematics 2011-09-29 Carlos Gorria , Miguel A. Alejo , Luis Vega

Control co-design (CCD) is a technique for improving the closed-loop performance of systems through the coordinated design of both plant parameters and an optimal control policy. While model predictive control (MPC) is an attractive control…

Systems and Control · Electrical Eng. & Systems 2023-04-18 Austin L. Nash , Herschel C. Pangborn , Neera Jain

Coordinate descent (CD) algorithms have become the method of choice for solving a number of optimization problems in machine learning. They are particularly popular for training linear models, including linear support vector machine…

Machine Learning · Statistics 2014-01-16 Tobias Glasmachers , Ürün Dogan
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