Contextual Bandits for Online Markdown Pricing for E-commerce-Reference-Cited by-同舟云学术

Contextual Bandits for Online Markdown Pricing for E-commerce

Published:2024-01-04 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 7th Joint International Conference on Data Science & Management of Data (11th ACM IKDD CODS and 29th COMAD)
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Author:

G Uma Maheswari¹^ORCID,Sethuraman Srividhya¹^ORCID,Ramanan Sharadha¹^ORCID

Affiliation:

1. TCS Research, India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3632410.3632448

Reference35 articles.

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2. Shipra Agrawal and Navin Goyal . Thompson sampling for contextual bandits with linear payoffs . In International conference on machine learning , pages 127– 135 . PMLR, 2013. Shipra Agrawal and Navin Goyal. Thompson sampling for contextual bandits with linear payoffs. In International conference on machine learning, pages 127–135. PMLR, 2013.

3. Ashwinkumar Badanidiyuru , Robert Kleinberg , and Aleksandrs Slivkins . Bandits with knapsacks. Journal of the ACM (JACM), 65(3):1–55 , 2018 . Ashwinkumar Badanidiyuru, Robert Kleinberg, and Aleksandrs Slivkins. Bandits with knapsacks. Journal of the ACM (JACM), 65(3):1–55, 2018.

4. Ashwinkumar Badanidiyuru , John Langford , and Aleksandrs Slivkins . Resourceful contextual bandits . In Conference on Learning Theory , pages 1109– 1134 . PMLR, 2014. Ashwinkumar Badanidiyuru, John Langford, and Aleksandrs Slivkins. Resourceful contextual bandits. In Conference on Learning Theory, pages 1109–1134. PMLR, 2014.

5. Rudolf Beran . Minimum hellinger distance estimates for parametric models. The annals of Statistics , pages 445– 463 , 1977 . Rudolf Beran. Minimum hellinger distance estimates for parametric models. The annals of Statistics, pages 445–463, 1977.