5 papers
Global Average Treatment Effects for Individualized Randomization Experiments with Aggregate Data
Shuguang Yu, Ting Li, Yuchen Lu +5
Individualized randomized experiments are central to online platforms for optimizing personalized decisions in complex environments. In two-sided markets, however, standard treatme…
Targeted Regularization for Causal Effect Estimation with Exponential Dispersion Family Outcomes
Jiahong Li, Zeqin Yang, Jixing Xu +4
Neural Networks (NNs) for causal effect estimation have shown strong empirical performance, yet endowing them with desirable semiparametric properties -- doubly robustness and fast…
Enhancing Ride-Hailing Forecasting at DiDi with Multi-View Geospatial Representation Learning from the Web
Xixuan Hao, Guicheng Li, Daiqiang Wu +6
The proliferation of ride-hailing services has fundamentally transformed urban mobility patterns, making accurate ride-hailing forecasting crucial for optimizing passenger experien…
Estimating Long-term Heterogeneous Dose-response Curve: Generalization Bound Leveraging Optimal Transport Weights
Zeqin Yang, Weilin Chen, Ruichu Cai +7
Long-term treatment effect estimation is a significant but challenging problem in many applications. Existing methods rely on ideal assumptions, such as no unobserved confounders o…
DFF: Decision-Focused Fine-tuning for Smarter Predict-then-Optimize with Limited Data
Jiaqi Yang, Enming Liang, Zicheng Su +5
Decision-focused learning (DFL) offers an end-to-end approach to the predict-then-optimize (PO) framework by training predictive models directly on decision loss (DL), enhancing de…