48 citations · 112 across the 14 of their papers we have counts for
4 papers · 1 filter
Modeling Heterogeneity in Mode-Switching Behavior Under a Mobility-on-Demand Transit System: An Interpretable Machine Learning Approach
Xilei Zhao, Xiang Yan, Pascal Van Hentenryck
Recent years have witnessed an increased focus on interpretability and the use of machine learning to inform policy analysis and decision making. This paper applies machine learnin…
Reinforcement Learning for Uplift Modeling
Chenchen Li, Xiang Yan, Xiaotie Deng +6
Uplift modeling aims to directly model the incremental impact of a treatment on an individual response. In this work, we address the problem from a new angle and reformulate it as…
Modeling Stated Preference for Mobility-on-Demand Transit: A Comparison of Machine Learning and Logit Models
Xilei Zhao, Xiang Yan, Alan Yu +1
Logit models are usually applied when studying individual travel behavior, i.e., to predict travel mode choice and to gain behavioral insights on traveler preferences. Recently, so…
Manipulation Robustness of Collaborative Filtering Systems
Xiang Yan, Benjamin Van Roy
A collaborative filtering system recommends to users products that similar users like. Collaborative filtering systems influence purchase decisions, and hence have become targets o…