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20092022
most citedConvergence rate bounds for a proximal ADMM with over-relaxation stepsize parameter for solving nonconvex linearly constrained problems

35 citations · 108 across the 23 of their papers we have counts for

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Showing 2020Show all

6 papers · 1 filter

math.OC2020

Iteration-complexity of a proximal augmented Lagrangian method for solving nonconvex composite optimization problems with nonlinear convex constraints

Weiwei Kong, Jefferson G. Melo, Renato D. C. Monteiro

This paper proposes and analyzes a proximal augmented Lagrangian (NL-IAPIAL) method for solving smooth nonconvex composite optimization problems with nonlinear -convex cons…

math.OC2020★ 1 cited

Iteration-complexity of an inner accelerated inexact proximal augmented Lagrangian method based on the classical Lagrangian function

Jefferson G. Melo, Renato D. C. Monteiro, Weiwei Kong

This paper establishes the iteration-complexity of an inner accelerated inexact proximal augmented Lagrangian (IAIPAL) method for solving linearly-constrained smooth nonconvex comp…

math.OC2020

Accelerated Inexact Composite Gradient Methods for Nonconvex Spectral Optimization Problems

Weiwei Kong, Renato D. C. Monteiro

This paper presents two inexact composite gradient methods, one inner accelerated and another doubly accelerated, for solving a class of nonconvex spectral composite optimization p…

math.OC2020★ 12 cited

Iteration-complexity of an inexact proximal accelerated augmented Lagrangian method for solving linearly constrained smooth nonconvex composite optimization problems

Jefferson G. Melo, Renato D. C. Monteiro, Hairong Wang

This paper proposes and establishes the iteration-complexity of an inexact proximal accelerated augmented Lagrangian (IPAAL) method for solving linearly constrained smooth nonconve…

math.OC2020★ 1 cited

Inexact cuts in SDDP applied to multistage stochastic nondifferentiable problems

Vincent Guigues, Renato Monteiro, Benar Svaiter

In [13], an Inexact variant of Stochastic Dual Dynamic Programming (SDDP) called ISDDP was introduced which uses approximate (instead of exact with SDDP) primal dual solutions of t…

math.OC2020★ 2 cited

A proximal bundle variant with optimal iteration-complexity for a large range of prox stepsizes

Jiaming Liang, Renato D. C. Monteiro

This paper presents a proximal bundle variant, namely, the relaxed proximal bundle (RPB) method, for solving convex nonsmooth composite optimization problems. Like other proximal b…