Dynamic Assortment Personalization in High Dimensions

@article{Kallus2016DynamicAP,
  title={Dynamic Assortment Personalization in High Dimensions},
  author={Nathan Kallus and Madeleine Udell},
  journal={arXiv: Machine Learning},
  year={2016}
}
  • Nathan Kallus, Madeleine Udell
  • Published 2016
  • Mathematics
  • arXiv: Machine Learning
  • We study the problem of dynamic assortment personalization with large, heterogeneous populations and wide arrays of products, and demonstrate the importance of structural priors for effective, efficient large-scale personalization. Assortment personalization is the problem of choosing, for each individual (type), a best assortment of products, ads, or other offerings (items) so as to maximize revenue. This problem is central to revenue management in e-commerce and online advertising where both… CONTINUE READING

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