Online Regularization toward Always-Valid High-Dimensional Dynamic Pricing
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Publication:6651394
DOI10.1080/01621459.2023.2284979MaRDI QIDQ6651394
Wei Sun, Zhanyu Wang, Guang Cheng, Unnamed Author
Publication date: 10 December 2024
Published in: Journal of the American Statistical Association (Search for Journal in Brave)
Cites Work
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- Statistics for high-dimensional data. Methods, theory and applications.
- Time-uniform Chernoff bounds via nonnegative supermartingales
- Dynamic Pricing with an Unknown Demand Model: Asymptotically Optimal Semi-Myopic Policies
- A Practical Scheme and Fast Algorithm to Tune the Lasso With Optimality Guarantees
- Dynamic Pricing Under a General Parametric Choice Model
- Optimal Auction Design
- High-Dimensional Statistics
- Statistical Inference for Online Decision Making via Stochastic Gradient Descent
- Contextual Search via Intrinsic Volumes
- Always Valid Inference: Continuous Monitoring of A/B Tests
- Online Decision Making with High-Dimensional Covariates
- Ridge Regression: Biased Estimation for Nonorthogonal Problems
- Statistical Inference for Online Decision Making: In a Contextual Bandit Setting
- A unified framework for high-dimensional analysis of \(M\)-estimators with decomposable regularizers
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