Optimal uncertainty quantification for legacy data observations of Lipschitz functions

@article{Sullivan2012OptimalUQ,
  title={Optimal uncertainty quantification for legacy data observations of Lipschitz functions},
  author={Timothy John Sullivan and Mike McKerns and Dominik Meyer and Florian Theil and Houman Owhadi and Michael Ortiz},
  journal={CoRR},
  year={2012},
  volume={abs/1202.1928}
}
We consider the problem of providing optimal uncertainty quantification (UQ) – and hence rigorous certification – for partially-observed functions. We present a UQ framework within which the observations may be small or large in number, and need not carry information about the probability distribution of the system in operation. The UQ objectives are posed as optimization problems, the solutions of which are optimal bounds on the quantities of interest; we consider two typical settings, namely… CONTINUE READING