4 papers · 1 filter
Contextual Online Pricing with (Biased) Offline Data
Yixuan Zhang, Ruihao Zhu, Qiaomin Xie
We study contextual online pricing with biased offline data. For the scalar price elasticity case, we identify the instance-dependent quantity that measures how far the offli…
Thompson Sampling for Repeated Newsvendor
Li Chen, Hanzhang Qin, Yunbei Xu +2
In this paper, we investigate the performance of Thompson Sampling (TS) for online learning with censored feedback, focusing primarily on the classic repeated newsvendor model--a f…
Efficient and Interpretable Bandit Algorithms
Subhojyoti Mukherjee, Ruihao Zhu, Branislav Kveton
Motivated by the importance of explainability in modern machine learning, we design bandit algorithms that are efficient and interpretable. A bandit algorithm is interpretable if i…
Learning to Price Supply Chain Contracts against a Learning Retailer
Xuejun Zhao, Ruihao Zhu, William B. Haskell
The rise of big data analytics has automated the decision-making of companies and increased supply chain agility. In this paper, we study the supply chain contract design problem f…