Pricing with High-Dimensional Data
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-01926-5_7
Reference22 articles.
1. Ban, G. Y., & Keskin, N. B. (2021). Personalized dynamic pricing with machine learning: High-dimensional features and heterogeneous elasticity. Management Science, 67(9), 5549–5568.
2. Ban, G. Y., & Rudin, C. (2019). The big data newsvendor: Practical insights from machine learning. Operations Research, 67(1), 90–108.
3. Ban, G. Y., Gallien, J., & Mersereau, A. J. (2019). Dynamic procurement of new products with covariate information: The residual tree method. Manufacturing & Service Operations Management, 21(4), 798–815.
4. Bastani, H., & Bayati, M. (2020). Online decision making with high-dimensional covariates. Operations Research, 68(1), 276–294.
5. Breiman, L. (2001). Random forests. Machine Learning, 45(1), 5–32.
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