research
∙
12/01/2022
Risk-Adaptive Approaches to Learning and Decision Making: A Survey
Uncertainty is prevalent in engineering design, statistical learning, an...
share
research
∙
08/20/2022
On Robustness in Nonconvex Optimization with Application to Defense Planning
In the context of structured nonconvex optimization, we estimate the inc...
research
∙
04/10/2022
Rockafellian Relaxation in Optimization under Uncertainty: Asymptotically Exact Formulations
In practice, optimization models are often prone to unavoidable inaccura...
research
∙
01/13/2022
Consistent Approximations in Composite Optimization
Approximations of optimization problems arise in computational procedure...
research
∙
09/12/2021
Gradients and Subgradients of Buffered Failure Probability
Gradients and subgradients are central to optimization and sensitivity a...
research
∙
07/22/2021
Data-driven optimization of reliability using buffered failure probability
Design and operation of complex engineering systems rely on reliability ...
research
∙
05/13/2021
Good and Bad Optimization Models: Insights from Rockafellians
A basic requirement for a mathematical model is often that its solution ...
research
∙
01/13/2021
Certifiable Risk-Based Engineering Design Optimization
Reliable, risk-averse design of complex engineering systems with optimiz...
research
∙
10/24/2019
