Online Regularization toward Always-Valid High-Dimensional Dynamic Pricing
Author:
Affiliation:
1. Department of Statistics, UCLA, Los Angeles, CA
2. Department of Statistics, Purdue University, West Lafayette, IN
3. Daniels School of Business, Purdue University, West Lafayette, IN
Funder
NSF-SES
The Office of Naval Research
NSF-SCALE MoDL
National Science Foundation
Publisher
Informa UK Limited
Subject
Statistics, Probability and Uncertainty,Statistics and Probability
Link
https://www.tandfonline.com/doi/pdf/10.1080/01621459.2023.2284979
Reference40 articles.
1. Personalized Dynamic Pricing with Machine Learning: High-Dimensional Features and Heterogeneous Elasticity
2. Online Decision Making with High-Dimensional Covariates
3. Meta Dynamic Pricing: Transfer Learning Across Experiments
4. Dynamic Pricing Under a General Parametric Choice Model
5. Bühlmann, P., and Van De Geer, S. (2011), Statistics for High-Dimensional Data: Methods, Theory and Applications, Berlin: Springer.
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