Research
Research Interests
- Statistical machine learning
- Large-scale optimal transport problems
- Subsampling methods in big data
- AI for healthcare
Publications
Junlie Huang, Xinlai Kang, Qiannan Huang, Mengyu Li & Cheng Meng (2025). Efficient approximation of leverage scores in two-dimensional autoregressive models with application to image anomaly detection. Journal of Computational and Graphical Statistics. In press.
Yukuan Hu, Mengyu Li, Xin Liu & Cheng Meng (2025). Sampling-based methods for multi-block optimization problems over transport polytopes. Mathematics of Computation, 94(353), 1281-1322. [paper]
Mengyu Li, Jun Yu, Tao Li & Cheng Meng (2024). Core-elements for large-scale least squares estimation. Statistics and Computing. 34(190). (Student Paper Award in 2022 JSM, Sections on Statistical Computing and Graphics). [paper] [code]
Mengyu Li, Jingyi Zhang & Cheng Meng (2024). Nonparametric additive models for billion observations. Journal of Computational and Graphical Statistics, 33(4), 1397–1412. [paper] [code]
Xinlai Kang, Mengyu Li, Xuqiang Chen, Fangyu Li & Cheng Meng (2023). A Hausdorff regression paradigm for interval privacy. IEEE Signal Processing Letters, 31, 146–150. [paper]
Mengyu Li, Jun Yu, Tao Li & Cheng Meng (2023). Importance sparsification for Sinkhorn algorithm. Journal of Machine Learning Research, 24(247), 1–44. (Student Paper Award in 2023 JSM, Statistics in Imaging Section). [paper] [code]
Mengyu Li, Jun Yu, Hongteng Xu & Cheng Meng (2023). Efficient approximation of Gromov-Wasserstein distance using importance sparsification. Journal of Computational and Graphical Statistics, 32(4), 1512–1523. [paper] [code]
Mengyu Li & Junlong Zhao (2022). Communication-efficient distributed linear discriminant analysis for binary classification. Statistica Sinica, 32, 1343–1361. [paper]