Research
Research Interests
(Hyper)graph network analysis and latent space methods
Statistical learning and inference on (hyper)graphs, high-dimensional statistics
Statistical machine learning for medical/economic research, natural/social science and psychometrics
Preprints
A latent space directed counting network model and its application to statistical journal citation data.
S. Wu, T. Zhang, G. Xu, J. Zhu, 2024.A general latent embedding approach for modeling high-dimensional hypergraphs.
S. Wu, G. Xu, J. Zhu, 2024.On sure early selection of the best subset.
Z. Zhu, S. Wu, 2021. arXiv.2107.06939 (under revision at IEEE Transactions on Information Theory)
Journal Publication
Supervised homogeneity fusion: a combinatorial approach.
W. Wang*, S. Wu*, Z. Zhu, L. Zhou, P.X.K. Song, 2022. The Annals of Statistics, 52(1): 285-310, 2024.A distributed community detection algorithm for large scale networks under stochastic block models.
S. Wu*, Z. Li*, X. Zhu, 2021. Computational Statistics and Data Analysis, vol. 187, 2023.
*: (co-) first author / equal contribution