Tight lower bounds on the convergence rate of primal-dual dynamics for equality constrained convex problems

IK Ozaslan, MR Jovanović - 2023 62nd IEEE Conference on …, 2023 - ieeexplore.ieee.org
We study the exponential stability of continuous-time primal-dual gradient flow dynamics for
convex optimization problems with linear equality constraints. Without making any …

On the global exponential stability of primal-dual dynamics for convex problems with linear equality constraints

IK Ozaslan, MR Jovanović - 2023 American Control …, 2023 - ieeexplore.ieee.org
We examine global exponential stability of the primal-dual gradient flow dynamics for
differentiable convex problems with linear equality constraints. We show that if the set of …

Accelerated forward–backward and Douglas–Rachford splitting dynamics

IK Ozaslan, MR Jovanović - Automatica, 2025 - Elsevier
We examine convergence properties of continuous-time variants of accelerated Forward–
Backward (FB) and Douglas–Rachford (DR) splitting algorithms for nonsmooth composite …

An Interconnected Systems Approach to Convergence Analysis of Discrete-Time Primal-Dual Algorithms

S Kelly, JW Simpson-Porco - 2024 American Control …, 2024 - ieeexplore.ieee.org
We study the geometric convergence rate of discrete-time primal-dual algorithms for solving
strongly-convex equality-constrained optimization problems. Our approach separates the …

Stability of Primal-Dual Gradient Flow Dynamics for Multi-Block Convex Optimization Problems

IK Ozaslan, P Patrinos, MR Jovanović - arxiv preprint arxiv:2408.15969, 2024 - arxiv.org
We examine stability properties of primal-dual gradient flow dynamics for composite convex
optimization problems with multiple, possibly nonsmooth, terms in the objective function …

A Unified Analysis of Saddle Flow Dynamics: Stability and Algorithm Design

P You, Y Liu, E Mallada - arxiv preprint arxiv:2409.05290, 2024 - arxiv.org
This work examines the conditions for asymptotic and exponential convergence of saddle
flow dynamics of convex-concave functions. First, we propose an observability-based …