Publications

You can also find my articles on my Google Scholar profile.

Papers

• Independent-Set Design of Experiments for Estimating Treatment and Spillover Effects under Network Interference. International Conference on Learning Representations (accepted). 2024. [arXiv]
  with Xu Zhang and Edoardo Airoldi.
• Semiparametric Tensor Factor Analysis by Iteratively Projected SVD. Journal of the Royal Statistical Society, Series B (in press) . 2023.[arXiv]
  with Elynn Chen, Dong Xia and Jianqing Fan.
• State Space Emulation and Annealed Sequential Monte Carlo for High Dimensional Optimization. Statistica Sinica (in press) . 2023. [Preprint]
  with Rong Chen.
• Resampling Strategy in Sequential Monte Carlo for Constrained Sampling Problems. Statistica Sinica (in press). 2023. [Preprint]
  with Rong Chen and Ming Lin.
• KoPA: Automated Kronecker Product Approximation. Journal of Machine Learning Research. 2022. [link]
  with Rong Chen and Han Xiao.
• Hybrid Kronecker Product Decomposition and Approximation. Journal of Computational and Graphical Statistics. 2022. [link]
  with Rong Chen and Han Xiao.
• Individualized Group Learning . Journal of the American Statistical Association. 2021. [link]
  with Rong Chen and Min-ge Xie.
• Individualized Inference through Fusion Learning. Wiley Interdisciplinary Reviews: Computational Statistics. 2020. [link]
  with Rong Chen and Min-ge Xie.
• iGroup Learning and iDetect for Dynamic Anomaly Detection with Applications in Maritime Threat Detection. 2018 IEEE International Symposium on Technologies for Homeland Security. [link]
  with Rong Chen, Alexander Liu, Fred Roberts and Min-ge Xie.

Manuscripts

• Optimizing Randomized and Deterministic Saturation Designs under Interference. [arXiv]
  with Jean Pouget-Abadie and Edoardo Airoldi.
• Matrix Completion using Kronecker Product Approximation. [arXiv]
  with Rong Chen and Han Xiao.
• Bullwhip Effect of Supply Networks: Joint Impact of Network Structure and Market Demand. [arXiv]
  with Jin-Zhu Yü and Jianxi Gao.
• Assessment of Accuracy of Finite Difference Methods in Evaluation of Options within Heston Model. [SSRN]