6 papers
Transfer Learning for Contextual Joint Assortment-Pricing under Cross-Market Heterogeneity
Elynn Chen, Xi Chen, Yi Zhang
We study transfer learning for contextual joint assortment-pricing under a multinomial logit choice model with bandit feedback. A seller operates across multiple related markets an…
High-Dimensional Linear Bandits under Stochastic Latent Heterogeneity
Elynn Chen, Xi Chen, Wenbo Jing +1
This paper addresses the critical challenge of stochastic latent heterogeneity in online decision-making, where individuals' responses to actions vary not only with observable cont…
Dynamic Contextual Pricing with Doubly Non-Parametric Random Utility Models
Elynn Chen, Xi Chen, Lan Gao +1
In the evolving landscape of digital commerce, adaptive dynamic pricing strategies are essential for gaining a competitive edge. This paper introduces novel {\em doubly nonparametr…
Distributed Tensor Principal Component Analysis with Data Heterogeneity
Elynn Chen, Xi Chen, Wenbo Jing +1
As tensors become widespread in modern data analysis, Tucker low-rank Principal Component Analysis (PCA) has become essential for dimensionality reduction and structural discovery…
Data-Driven Knowledge Transfer in Batch Learning
Elynn Chen, Xi Chen, Wenbo Jing
In data-driven decision-making in marketing, healthcare, and education, it is desirable to utilize a large amount of data from existing ventures to navigate high-dimensional featur…
MEV Makes Everyone Happy under Greedy Sequencing Rule
Yuhao Li, Mengqian Zhang, Jichen Li +3
Trading through decentralized exchanges (DEXs) has become crucial in today's blockchain ecosystem, enabling users to swap tokens efficiently and automatically. However, the capacit…