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Primal–Dual Stability in Local Optimality
Much is known about when a locally optimal solution depends in a single-valued Lipschitz continuous way on the problem’s parameters, including tilt...
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An Inexact Primal-Dual Smoothing Framework for Large-Scale Non-Bilinear Saddle Point Problems
We develop an inexact primal-dual first-order smoothing framework to solve a class of non-bilinear saddle point problems with primal strong...
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A Primal-dual Backward Reflected Forward Splitting Algorithm for Structured Monotone Inclusions
We propose a primal-dual backward reflected forward splitting method for solving structured primal-dual monotone inclusions in real Hilbert spaces....
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Primal-Dual Algorithm for Distributed Optimization with Coupled Constraints
This paper focuses on distributed consensus optimization problems with coupled constraints over time-varying multi-agent networks, where the global...
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Time Rescaling of a Primal-Dual Dynamical System with Asymptotically Vanishing Dam**
In this work, we approach the minimization of a continuously differentiable convex function under linear equality constraints by a second-order...
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Stable Convergence of a Primal-Dual Method for Multi-agent Optimization Problems
AbstractWe describe a class of primal-dual methods for convex constrained multi-agent optimization problems. We show that these methods possess...
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A Second Order Primal–Dual Dynamical System for a Convex–Concave Bilinear Saddle Point Problem
The class of convex–concave bilinear saddle point problems encompasses many important convex optimization models arising in a wide array of...
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A Universal Accelerated Primal–Dual Method for Convex Optimization Problems
This work presents a universal accelerated primal–dual method for affinely constrained convex optimization problems. It can handle both Lipschitz and...
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A partially inexact generalized primal-dual hybrid gradient method for saddle point problems with bilinear couplings
One of the most popular algorithms for saddle point problems is the so-named primal-dual hybrid gradient method, which have been received much...
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A fast primal-dual algorithm via dynamical system with variable mass for linearly constrained convex optimization
We aim to solve the linearly constrained convex optimization problem whose objective function is the sum of a differentiable function and a...
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Chambolle–Pock’s Primal-Dual Method with Mismatched Adjoint
The primal-dual method of Chambolle and Pock is a widely used algorithm to solve various optimization problems written as convex-concave saddle point...
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A nonsmooth primal-dual method with interwoven PDE constraint solver
We introduce an efficient first-order primal-dual method for the solution of nonsmooth PDE-constrained optimization problems. We achieve this...
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IPRSDP: a primal-dual interior-point relaxation algorithm for semidefinite programming
We propose an efficient primal-dual interior-point relaxation algorithm based on a smoothing barrier augmented Lagrangian, called IPRSDP, for solving...
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An efficient primal-dual interior point algorithm for convex quadratic semidefinite optimization
We introduce a primal-dual interior point algorithm for convex quadratic semidefinite optimization. This algorithm is based on an extension of the...
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Primal-dual active set method for evaluating American put options on zero-coupon bonds
An efficient numerical method is propoesd for a parabolic linear complementarity problem (LCP) arising in the valuation of American options on...
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A nested primal–dual FISTA-like scheme for composite convex optimization problems
We propose a nested primal–dual algorithm with extrapolation on the primal variable suited for minimizing the sum of two convex functions, one of...
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A Unified Primal-Dual Algorithm Framework for Inequality Constrained Problems
In this paper, we propose a unified primal-dual algorithm framework based on the augmented Lagrangian function for composite convex problems with...
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Primal-Dual ε-Subgradient Method for Distributed Optimization
This paper studies the distributed optimization problem when the objective functions might be nondifferentiable and subject to heterogeneous set...
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Faster first-order primal-dual methods for linear programming using restarts and sharpness
First-order primal-dual methods are appealing for their low memory overhead, fast iterations, and effective parallelization. However, they are often...
