3 papers
math.OC2026
Multi-cut stochastic approximation methods for solving stochastic convex composite optimization
Jiaming Liang, Renato D. C. Monteiro, Honghao Zhang
This paper considers the stochastic convex composite optimization problem and presents multi-cut stochastic approximation (SA) methods for solving it, whose models in expectation o…
math.OC2025
Universal subgradient and proximal bundle methods for convex and strongly convex hybrid composite optimization
Vincent Guigues, Jiaming Liang, Renato D. C. Monteiro
This paper develops two parameter-free methods for solving convex and strongly convex hybrid composite optimization problems, namely, a composite subgradient type method and a prox…
math.OC2024
Parameter-free proximal bundle methods with adaptive stepsizes for hybrid convex composite optimization problems
Renato D. C. Monteiro, Honghao Zhang
This paper develops a parameter-free adaptive proximal bundle method with two important features: 1) adaptive choice of variable prox stepsizes that "closely fits" the instance und…