{"title":"A Second Order Primal–Dual Dynamical System for a Convex–Concave Bilinear Saddle Point Problem","authors":"Xin He, Rong Hu, Yaping Fang","doi":"10.1007/s00245-023-10102-5","DOIUrl":null,"url":null,"abstract":"<div><p>The class of convex–concave bilinear saddle point problems encompasses many important convex optimization models arising in a wide array of applications. The most of existing primal–dual dynamical systems for saddle point problems are based on first order ordinary differential equations (ODEs), which only own the <span>\\({\\mathcal {O}}(1/t)\\)</span> convergence rate in the convex case, and fast convergence rate analysis always requires some additional assumption such as strong convexity. In this paper, based on second order ODEs, we consider a general inertial primal–dual dynamical system, with damping, scaling and extrapolation coefficients, for a convex–concave bilinear saddle point problem. By the Lyapunov analysis approach, under appropriate assumptions, we investigate the convergence rates of the primal–dual gap and velocities, and the boundedness of the trajectories for the proposed dynamical system. With special parameters, our results can recover the Polyak’s heavy ball acceleration scheme and Nesterov’s acceleration scheme. We also provide numerical examples to support our theoretical claims.</p></div>","PeriodicalId":55566,"journal":{"name":"Applied Mathematics and Optimization","volume":"89 2","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Mathematics and Optimization","FirstCategoryId":"100","ListUrlMain":"https://link.springer.com/article/10.1007/s00245-023-10102-5","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
The class of convex–concave bilinear saddle point problems encompasses many important convex optimization models arising in a wide array of applications. The most of existing primal–dual dynamical systems for saddle point problems are based on first order ordinary differential equations (ODEs), which only own the \({\mathcal {O}}(1/t)\) convergence rate in the convex case, and fast convergence rate analysis always requires some additional assumption such as strong convexity. In this paper, based on second order ODEs, we consider a general inertial primal–dual dynamical system, with damping, scaling and extrapolation coefficients, for a convex–concave bilinear saddle point problem. By the Lyapunov analysis approach, under appropriate assumptions, we investigate the convergence rates of the primal–dual gap and velocities, and the boundedness of the trajectories for the proposed dynamical system. With special parameters, our results can recover the Polyak’s heavy ball acceleration scheme and Nesterov’s acceleration scheme. We also provide numerical examples to support our theoretical claims.
期刊介绍:
The Applied Mathematics and Optimization Journal covers a broad range of mathematical methods in particular those that bridge with optimization and have some connection with applications. Core topics include calculus of variations, partial differential equations, stochastic control, optimization of deterministic or stochastic systems in discrete or continuous time, homogenization, control theory, mean field games, dynamic games and optimal transport. Algorithmic, data analytic, machine learning and numerical methods which support the modeling and analysis of optimization problems are encouraged. Of great interest are papers which show some novel idea in either the theory or model which include some connection with potential applications in science and engineering.