Phi-Divergence Constrained Ambiguous Stochastic Programs for Data-Driven Optimization


This paper investigates the use of φ-divergences in ambiguous (or distributionally robust) two-stage stochastic programs. Classical stochastic programming assumes the distribution of uncertain parameters are known. However, the true distribution is unknown in many applications. Especially in cases where there is little data or not much trust in the data, an… (More)


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