WebMay 1, 2011 · In this paper we study a first-order primal-dual algorithm for non-smooth convex optimization problems with known saddle-point structure. We prove convergence to a saddle-point with rate O (1/ N ) in finite dimensions for the complete class of problems.We further show accelerations of the proposed algorithm to yield improved rates on … WebOct 25, 2024 · In this study, we introduce a primal-dual prediction-correction algorithm framework for convex optimization problems with known saddle-point structure. Our unified frame adds the proximal term with a positive definite weighting matrix.
A Semidefinite Relaxation Method for Elliptical Location
WebApr 10, 2024 · In this paper, we propose a variance-reduced primal-dual algorithm with Bregman distance functions for solving convex-concave saddle-point problems with finite-sum structure and nonbilinear coupling function. This type of problem typically arises in machine learning and game theory. Based on some standard assumptions, the … WebPrimal affine and primal-dual algorithms are linear (not nonlinear) programming procedures. To create a linear program suitable for application of these algorithms, the integrals in the L 1 spline functionals need to be discretized. For the primal affine algorithm used in the present paper and in [5,6,8,10,11], the spline functionals were ... new class primarysource
FlexPD: A Flexible Framework of First-Order Primal-Dual Algorithms …
WebIn this paper we study preconditioning techniques for the first-order primal-dual algorithm proposed in [5]. In particular, we propose simple and easy to compute diagonal preconditioners for which convergence of the algorithm is guaranteed without the need to compute any step size parameters. As a by-product, we show that for a certain instance … WebDec 21, 2010 · In this paper we study a first-order primal-dual algorithm for non-smooth convex optimization problems with known saddle-point structure. We prove … WebLinear Convergence of First- and Zeroth-Order Primal–Dual Algorithms for Distributed Nonconvex Optimization Abstract: This article considers the distributed nonconvex … new class proposal