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Discipline of Operations Management and Econometrics


Dr Thomas A. Weber, Stanford University

1st Nov 2010  12:00 pm - Room 498, Merewether Building

Separating the identification problem from the problem of finding solutions to a decision problem described by an uncertain model has the generic drawback that the error norm used for fitting the model is not related to the expected loss from ex-post model mismatch. Furthermore, sample data from the model can be often complemented by insights about admissible model behavior. In this talk, I will present a general approach that merges the identification and robust optimization problems, subject to structural constraints. Approximation errors and optimal decisions are determined simultaneously, together with an ex-ante distribution of the corresponding payoffs. I will also discuss the related problem of data acquisition and provide perspectives on how the approach can be generalized to games. The robust approximation method is illustrated for the problem of optimal debt settlement in the credit-card industry.

Joint work with Naveed Chehrazi.