Uncertainty is prevalent in engineering design, statistical learning, an...
In the context of structured nonconvex optimization, we estimate the inc...
In practice, optimization models are often prone to unavoidable inaccura...
Approximations of optimization problems arise in computational procedure...
Gradients and subgradients are central to optimization and sensitivity
a...
Design and operation of complex engineering systems rely on reliability
...
A basic requirement for a mathematical model is often that its solution
...
Reliable, risk-averse design of complex engineering systems with optimiz...
The theoretical and empirical performance of Empirical Risk Minimization...