Publications

Representative Works

The following works best describe who I am as a researcher. For a list of complete works, see my CV.

Note: * indicates co-first authors

0. A Distributionally Robust Instrumental Variables Estimation Framework

with Yongchan Kwon. Working Paper (2024).

1. A Bias-Variance Trade-off Framework for Data with Non-negative Outcome Variables

with Agostino Capponi. Working Paper (2024).

2. Inferring Dynamic Networks from Marginals with Iterative Proportional Fitting

with Serina Chang*, Frederic Koehler*, Jure Leskovec, and Johan Ugander. 41st International Conference on Machine Learning (ICML) (2024).

3. On Sinkhorn’s Algorithm and Choice Modeling

with Alfred Galichon and Johan Ugander. Under Revision at Operations Research (2023).

4. Computationally Efficient Estimation of Large Probit Models

with Patrick Ding, Guido Imbens, and Yinyu Ye. Under Review (2023).

5. Optimal Diagonal Preconditioning

with Wenzhi Gao*, Oliver Hinder, Yinyu Ye, and Zhengyuan Zhou. Operations Research (2023).

6. Semiparametric Estimation of Treatment Effects in Observational Studies with Heterogeneous Partial Interference

with Ruoxuan Xiong*, Jizhou Liu, and Guido Imbens. Under Revision at Journal of Business and Economic Statistics (2024).

7. A Unified Linear Speedup Analysis of Federated Averaging and Nesterov FedAvg

with Kaixiang Lin*, Zhaojian Li, Jiayu Zhou, and Zhengyuan Zhou. Journal of Artificial Intelligence Research 78: 1143-1200 (2023).

8. Ensemble Methods for Causal Effects in Panel Data Settings

with Susan Athey, Mohsen Bayati, and Guido Imbens. American Economic Association Papers and Proceedings 109: 65-70 (2019).