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In this note, we propose a FISTA-type first order algorithm, VAR-FISTA, to solve a composite optimization problem. A distinctive feature of VAR-FISTA is its ability to exploit the convexity of the function in the problem, resulting in an…

Optimization and Control · Mathematics 2020-08-25 Chee-Khian Sim

Obtaining the inverse of a large symmetric positive definite matrix $\mathcal{A}\in\mathbb{R}^{p\times p}$ is a continual challenge across many mathematical disciplines. The computational complexity associated with direct methods can be…

Numerical Analysis · Mathematics 2025-09-03 Ann Paterson , Jennifer Pestana , Victorita Dolean

Numerous practical medical problems often involve data that possess a combination of both sparse and non-sparse structures. Traditional penalized regularizations techniques, primarily designed for promoting sparsity, are inadequate to…

Methodology · Statistics 2023-11-10 Shun Yu , Yuehan Yang

In this article, a new category of soft-input soft-output (SISO) minimum-mean square error (MMSE) finite-impulse response (FIR) decision feedback equalizers (DFEs) with iteration-wise static filters (i.e. iteration variant) is investigated.…

Signal Processing · Electrical Eng. & Systems 2020-01-29 Serdar Şahin , Antonio Maria Cipriano , Charly Poulliat , Marie-Laure Boucheret

The sequential fully implicit (SFI) scheme was introduced (Jenny et al. 2006) for solving coupled flow and transport problems. Each time step for SFI consists of an outer loop, in which there are inner Newton loops to implicitly and…

Numerical Analysis · Mathematics 2021-08-05 Jiamin Jiang , Pavel Tomin , Yifan Zhou

In this paper, we propose a simple yet efficient strategy for improving the multi-objective steepest descent method proposed by Fliege and Svaiter (Math Methods Oper Res, 2000, 3: 479--494). The core idea behind this strategy involves…

Optimization and Control · Mathematics 2024-01-15 Wang Chen , Liping Tang , Xinmin Yang

Multi-block separable convex problems recently received considerable attention. This class of optimization problems minimizes a separable convex objective function with linear constraints. The algorithmic challenges come from the fact that…

Optimization and Control · Mathematics 2016-08-18 Qia Li , Yuesheng Xu , Na Zhang

Over the past decade, Finite Element Method (FEM) has served as a foundational numerical framework for approximating the terms of Time Series Expansion (TSE) as solutions to transient Partial Differential Equation (PDE). However, the…

Numerical Analysis · Mathematics 2024-09-04 Ahmad Deeb , Denys Dutykh

Considered here is an efficient technique to compute approximate profiles of solitary wave solutions of fractional Korteweg-de Vries equations. The numerical method is based on a fixed-point iterative algorithm along with extrapolation…

Numerical Analysis · Mathematics 2017-04-28 A. Duran

Variational regularization of ill-posed inverse problems is based on minimizing the sum of a data fidelity term and a regularization term. The balance between them is tuned using a positive regularization parameter, whose automatic choice…

Numerical Analysis · Mathematics 2025-11-12 Markus Juvonen , Bjørn Jensen , Ilmari Pohjola , Yiqiu Dong , Samuli Siltanen

We present a family of fast and accurate Dijkstra-like solvers for the eikonal equation and factored eikonal equation which compute solutions on a regular grid by solving local variational minimization problems. Our methods converge…

Numerical Analysis · Mathematics 2019-09-06 Samuel F. Potter , Maria K. Cameron

A new consistent, spatially adaptive, smoothed particle hydrodynamics (SPH) method for Fluid-Structure Interactions (FSI) is presented. The method combines several attributes that have not been simultaneously satisfied by other SPH methods.…

Fluid Dynamics · Physics 2019-02-20 Wei Hu , Guannan Guo , Xiaozhe Hu , Dan Negrut , Zhijie Xu , Wenxiao Pan

Federated learning aggregates model updates from distributed clients, but standard first order methods such as FedAvg apply the same scalar weight to all parameters from each client. Under non-IID data, these uniformly weighted updates can…

Machine Learning · Computer Science 2026-01-21 Zhipeng Chang , Ting He , Wenrui Hao

The First-Order Variable Elimination (FOVE) algorithm allows exact inference to be applied directly to probabilistic relational models, and has proven to be vastly superior to the application of standard inference methods on a grounded…

Artificial Intelligence · Computer Science 2012-02-20 Udi Apsel , Ronen I. Brafman

As first-order optimization methods become the method of choice for solving large-scale optimization problems, optimization solvers based on first-order algorithms are being built. Such general-purpose solvers must robustly detect…

Optimization and Control · Mathematics 2023-03-29 Jisun Park , Ernest K. Ryu

This study presents a novel mixed-precision iterative refinement algorithm, GADI-IR, within the general alternating-direction implicit (GADI) framework, designed for efficiently solving large-scale sparse linear systems. By employing…

Numerical Analysis · Mathematics 2025-03-24 Jifeng Ge , Juan Zhang

Nonlinear eigenvalue problems (NEPs) present significant challenges due to their inherent complexity and the limitations of traditional linear eigenvalue theory. This paper addresses these challenges by introducing a nonlinear…

Numerical Analysis · Mathematics 2024-09-18 Ronald Katende

In this article we study adaptive finite element methods (AFEM) with inexact solvers for a class of semilinear elliptic interface problems. We are particularly interested in nonlinear problems with discontinuous diffusion coefficients, such…

Numerical Analysis · Mathematics 2016-08-24 Michael Holst , Ryan Szypowski , Yunrong Zhu

Fluid-Structure Interaction (FSI) is a crucial problem in ocean engineering. The smoothed particle hydrodynamics (SPH) method has been employed recently for FSI problems in light of its Lagrangian nature and its advantage in handling…

Fluid Dynamics · Physics 2023-07-19 Tianrun Gao , Huihe Qiu , Lin Fu

This paper describes a regularized variant of the alternating direction method of multipliers (ADMM) for solving linearly constrained convex programs. It is shown that the pointwise iteration-complexity of the new method is better than the…

Optimization and Control · Mathematics 2017-01-09 Max L. N. Goncalves , Jefferson G. Melo , Renato D. C. Monteiro