Warren Hare – The University of British Columbia, Canada
A blackbox is a function that provides output without explanation of how the output was constructed. One common strategy for optimization involving blackbox functions is to numerically approximate gradients and/or Hessians and use these approximations in a classical method. In this talk, we examine the mathematical theory behind such an approach. We discuss classical and novel approximation techniques for blackbox functions. And, we illustrate the results on a case study from an application in Medical Physics.
Campus de l'Université de Montréal
2920, chemin de la Tour
Montréal Québec H3T 1J4