This is a preview. Log in through your library . Abstract For high dimensional problems, such as approximation and integration, one cannot afford to sample on a grid because of the curse of ...

For many decision-making problems under uncertainty, it is crucial to develop risk-averse models and specify the decision makers' risk preferences based on multiple stochastic performance measures (or ...