25 citations · 33 across the 27 of their papers we have counts for
4 papers · 1 filter
Lipschitzian SLLNs for random functions
Lai Tian, Johannes O. Royset
We prove strong laws of large numbers for random functions in the Lipschitz pseudometric. Our results hold under either a topological or a model-theoretic condition, with the latte…
Perturbation Duality for Robust and Distributionally Robust Optimization: Short and General Proofs
Louis L. Chen, Jake Roth, Johannes O. Royset
Duality is a foundational tool in robust and distributionally robust optimization (RO/DRO), underpinning both analytical insights and tractable reformulations. Whereas RO/DRO duali…
Composite Optimization using Local Models and Global Approximations
Welington de Oliveira, Johannes O. Royset
This work presents a unified framework that combines global approximations with locally built models to handle challenging nonconvex and nonsmooth composite optimization problems,…
Optimistic Bilevel Optimization with Composite Lower-Level Problem
Mattia Solla, Johannes O. Royset
This paper introduces a novel double regularization scheme for bilevel optimization problems whose lower-level problem is composite and convex, but not necessarily strongly convex,…