# Data-Pooling in Stochastic Optimization

@article{Gupta2019DataPoolingIS, title={Data-Pooling in Stochastic Optimization}, author={Vishal Gupta and Nathan Kallus}, journal={Computational Materials Science eJournal}, year={2019} }

Managing large-scale systems often involves simultaneously solving thousands of unrelated stochastic optimization problems, each with limited data. Intuition suggests one can decouple these unrelated problems and solve them separately without loss of generality. We propose a novel data-pooling algorithm called Shrunken-SAA that disproves this intuition. In particular, we prove that combining data across problems can outperform decoupling, even when there is no a priori structure linking the… CONTINUE READING

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