作者：Bertsimas, Dimitris; Mundru, Nishanth
作者单位：Massachusetts Institute of Technology (MIT)
摘要：We propose a novel, optimization-based method that takes into account the objective and problem structure for reducing the number of scenarios, m, needed for solving two-stage stochastic optimization problems. We develop a corresponding convex optimization-based algorithm and show that, as the number of scenarios increase, the proposed method recovers the SAA solution. We report computational results with both synthetic and real-world data sets that show that the proposed method has significan...
作者：Yoo, Onesun Steve; Zhan, Dongyuan
作者单位：University of London; University College London
摘要：A critical issue in operating massive open online courses (MOOCs) is the scalability of providing feedback. Because it is not feasible for instructors to grade a large number of students' assignments, MOOCs use peer grading systems. This study investigates the efficacy of that practice when student graders are rational economic agents. We characterize grading as a process of (a) acquiring information to assess an assignment's quality and (b) reporting a score. This process entails a tradeoff b...
