Jeff L Hong

Ambiguous Probabilistic Programs

  • Jeff L Hong
  • Anthony Man-Cho So
  • Zhaolin Hu
    • Categories Robust Optimization, Stochastic Programming Tags , , ,

    Probabilistic programs are widely used decision models. When implemented in practice, however, there often exists distributional ambiguity in these models. In this paper, we model the ambiguity using the likelihood ratio (LR) and use LR to construct various ambiguity sets. We consider ambiguous probabilistic programs which optimize under the worst case. Ambiguous probabilistic programs can … Read more

    Kullback-Leibler Divergence Constrained Distributionally Robust Optimization

  • Jeff L Hong
  • Zhaolin Hu
    • Categories Nonlinear Optimization, Robust Optimization, Stochastic Programming

    In this paper we study distributionally robust optimization (DRO) problems where the ambiguity set of the probability distribution is defined by the Kullback-Leibler (KL) divergence. We consider DRO problems where the ambiguity is in the objective function, which takes a form of an expectation, and show that the resulted minimax DRO problems can be formulated … Read more