Non-stationary First-Order Primal-Dual Algorithms with Faster Convergence Rates
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Publication:4971027
DOI10.1137/19M1293855zbMath1451.90126arXiv1903.05282MaRDI QIDQ4971027
Publication date: 8 October 2020
Published in: SIAM Journal on Optimization (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1903.05282
constrained convex optimizationfast convergence ratescomposite convex minimizationnon-ergodic convergence ratenon-stationary primal-dual method
Convex programming (90C25) Large-scale problems in mathematical programming (90C06) Computational methods for problems pertaining to operations research and mathematical programming (90-08)
Related Items (8)
A new randomized primal-dual algorithm for convex optimization with fast last iterate convergence rates ⋮ A unified convergence rate analysis of the accelerated smoothed gap reduction algorithm ⋮ New Primal-Dual Algorithms for a Class of Nonsmooth and Nonlinear Convex-Concave Minimax Problems ⋮ A Two-Stage Color Image Segmentation Method Based on Saturation-Value Total Variation ⋮ Inertial accelerated primal-dual methods for linear equality constrained convex optimization problems ⋮ A golden ratio proximal alternating direction method of multipliers for separable convex optimization ⋮ Transformed primal-dual methods for nonlinear saddle point systems ⋮ A primal-dual flow for affine constrained convex optimization
Uses Software
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