Asymptotic convergence of constrained primal-dual dynamics
Not on the map. Why?
Abstract (arXiv)
This paper studies the asymptotic convergence properties of the primal-dual dynamics designed for solving constrained concave optimization problems using classical notions from stability analysis. We motivate the need for this study by providing an example that rules out the possibility of employing the invariance principle for hybrid automata to study asymptotic convergence. We understand the solutions of the primal-dual dynamics in the Caratheodory sense and characterize their existence, uniqueness, and continuity with respect to the initial condition. We use the invariance principle for discontinuous Caratheodory systems to establish that the primal-dual optimizers are globally asymptotically stable under the primal-dual dynamics and that each solution of the dynamics converges to an optimizer.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 Oct 2015.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2022: 1; 2023: 0; 2024: 3; 2025: 1; 2026: 3.
8 papers.
- 2024Constrained Sampling with Primal-Dual Langevin Monte Carlocited by 10
- 2025Learning (Approximately) Equivariant Networks via Constrained Optimizationcited by 10
- 2022Constrained Reinforcement Learning via Dissipative Saddle Flow Dynamicscited by 3
- 2026Fully Distributed GNE Algorithms for Multi-Robot Placement without Consensus on Multiplierscited by 1
- 2024Stability of Primal-Dual Gradient Flow Dynamics for Multi-Block Convex Optimization Problemscited by 0
- 2024Provable Accuracy Bounds for Hybrid Dynamical Optimization and Samplingcited by 0
- 2026Residual-Controlled Multiplier Learning for Stochastic Constrained Decision-Makingcited by 0
- 2026Input-to-State Stability Framework for Fully Distributed Primal-Dual Dynamics for Quadratic GNEPs Without Multiplier Consensuscited by 0
- 2026Input-to-State Stability Framework for Fully Distributed Primal-Dual Dynamics for Quadratic GNEPs Without Multiplier Consensus7 Sep 2026
- 2026Fully Distributed GNE Algorithms for Multi-Robot Placement without Consensus on Multipliers29 Aug 2026
- 2026Residual-Controlled Multiplier Learning for Stochastic Constrained Decision-Making5 Jun 2026
- 2025Learning (Approximately) Equivariant Networks via Constrained Optimization19 May 2025
- 2024Constrained Sampling with Primal-Dual Langevin Monte Carlo1 Nov 2024
- 2024Provable Accuracy Bounds for Hybrid Dynamical Optimization and Sampling8 Oct 2024
- 2024Stability of Primal-Dual Gradient Flow Dynamics for Multi-Block Convex Optimization Problems28 Aug 2024
- 2022Constrained Reinforcement Learning via Dissipative Saddle Flow Dynamics3 Dec 2022