Online Decision Making with High-Dimensional Covariates

Citations

Cited by:

1. Yining Wang & Boxiao Chen & David Simchi-Levi, 2021. "Multimodal Dynamic Pricing," Management Science, INFORMS, vol. 67(10), pages 6136-6152, October.
2. Kimia Keshanian & Daniel Zantedeschi & Kaushik Dutta, 2022. "Features Selection as a Nash-Bargaining Solution: Applications in Online Advertising and Information Systems," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2485-2501, September.
3. Xi Chen & Quanquan Liu & Yining Wang, 2023. "Active Learning for Contextual Search with Binary Feedback," Management Science, INFORMS, vol. 69(4), pages 2165-2181, April.
4. Oliveira, Fabio & Kakabadse, Nada & Khan, Nadeem, 2022. "Board engagement with digital technologies: A resource dependence framework," Journal of Business Research, Elsevier, vol. 139(C), pages 804-818.
5. Long He & Sheng Liu & Zuo‐Jun Max Shen, 2022. "Smart urban transport and logistics: A business analytics perspective," Production and Operations Management, Production and Operations Management Society, vol. 31(10), pages 3771-3787, October.
6. Hamsa Bastani & Kimon Drakopoulos & Vishal Gupta & Jon Vlachogiannis & Christos Hadjichristodoulou & Pagona Lagiou & Gkikas Magiorkinis & Dimitrios Paraskevis & Sotirios Tsiodras, 2022. "Interpretable Operations Research for High-Stakes Decisions: Designing the Greek COVID-19 Testing System," Interfaces, INFORMS, vol. 52(5), pages 398-411, September.
7. Jean-Marie John-Mathews & Dominique Cardon & Christine Balagué, 2022. "From Reality to World. A Critical Perspective on AI Fairness," Journal of Business Ethics, Springer, vol. 178(4), pages 945-959, July.
8. Jingwen Zhang & Yifang Chen & Amandeep Singh, 2022. "Causal Bandits: Online Decision-Making in Endogenous Settings," Papers 2211.08649, arXiv.org, revised Feb 2023.
9. Ruohan Zhan & Zhimei Ren & Susan Athey & Zhengyuan Zhou, 2024. "Policy Learning with Adaptively Collected Data," Management Science, INFORMS, vol. 70(8), pages 5270-5297, August.
   • Ruohan Zhan & Zhimei Ren & Susan Athey & Zhengyuan Zhou, 2021. "Policy Learning with Adaptively Collected Data," Papers 2105.02344, arXiv.org, revised Nov 2022.
   • Zhan, Ruohan & Ren, Zhimei & Athey, Susan & Zhou, Zhengyuan, 2021. "Policy Learning with Adaptively Collected Data," Research Papers 3963, Stanford University, Graduate School of Business.
10. Yinchu Zhu & Ilya O. Ryzhov, 2022. "Optimal data-driven hiring with equity for underrepresented groups," Papers 2206.09300, arXiv.org.
11. Anthony Bonifonte & Turgay Ayer & Benjamin Haaland, 2022. "An Analytics Approach to Guide Randomized Controlled Trials in Hypertension Management," Management Science, INFORMS, vol. 68(9), pages 6634-6647, September.
12. Arlen Dean & Amirhossein Meisami & Henry Lam & Mark P. Van Oyen & Christopher Stromblad & Nick Kastango, 2022. "Quantile regression forests for individualized surgery scheduling," Health Care Management Science, Springer, vol. 25(4), pages 682-709, December.
13. Yichun Hu & Nathan Kallus & Xiaojie Mao, 2022. "Fast Rates for Contextual Linear Optimization," Management Science, INFORMS, vol. 68(6), pages 4236-4245, June.
14. Nathan Kallus & Xiaojie Mao & Angela Zhou, 2022. "Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination," Management Science, INFORMS, vol. 68(3), pages 1959-1981, March.
15. Farzad Pourbabaee, 2021. "High Dimensional Decision Making, Upper and Lower Bounds," Papers 2105.00545, arXiv.org.
16. He Jiang, 2023. "Forecasting global solar radiation using a robust regularization approach with mixture kernels," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 1989-2010, December.
17. Rong Jin & David Simchi-Levi & Li Wang & Xinshang Wang & Sen Yang, 2021. "Shrinking the Upper Confidence Bound: A Dynamic Product Selection Problem for Urban Warehouses," Management Science, INFORMS, vol. 67(8), pages 4756-4771, August.
18. Ying Zhong & L. Jeff Hong & Guangwu Liu, 2021. "Earning and Learning with Varying Cost," Production and Operations Management, Production and Operations Management Society, vol. 30(8), pages 2379-2394, August.
19. Singha, Sumanta & Arha, Himanshu & Kar, Arpan Kumar, 2023. "Healthcare analytics: A techno-functional perspective," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
20. Francis de Véricourt & Georgia Perakis, 2020. "Frontiers in Service Science: The Management of Data Analytics Services: New Challenges and Future Directions," Service Science, INFORMS, vol. 12(4), pages 121-129, December.
21. Pourbabaee, Farzad, 2021. "High dimensional decision making, upper and lower bounds," Economics Letters, Elsevier, vol. 204(C).
22. Masahiro Kato & Shinji Ito, 2023. "Best-of-Both-Worlds Linear Contextual Bandits," Papers 2312.16489, arXiv.org.
23. Ningyuan Chen & Guillermo Gallego, 2021. "Nonparametric Pricing Analytics with Customer Covariates," Operations Research, INFORMS, vol. 69(3), pages 974-984, May.
24. Stephen E. Chick & Noah Gans & Özge Yapar, 2022. "Bayesian Sequential Learning for Clinical Trials of Multiple Correlated Medical Interventions," Management Science, INFORMS, vol. 68(7), pages 4919-4938, July.
25. Xijin Chen & Kim May Lee & Sofia S Villar & David S Robertson, 2022. "Some performance considerations when using multi-armed bandit algorithms in the presence of missing data," PLOS ONE, Public Library of Science, vol. 17(9), pages 1-28, September.
26. Claudio Cardoso Flores & Marcelo Cunha Medeiros, 2020. "Online Action Learning in High Dimensions: A Conservative Perspective," Papers 2009.13961, arXiv.org, revised Mar 2024.