Zheng (Tracy) Ke

Selected Publications on Network Data Analysis

Survey paper:

• Ke, Z. and Jin J. (2023).
  Special Invited Paper: The SCORE Normalization, Especially for Heterogeneous Network and Text Data. (website, arXiv, pdf)
  Stat, 12(1), e545.
  

Editor's invited discussion paper:

• Ji, P., Jin, J., Ke, Z. and Li, W. (2022).
  Co-citation and Co-authorship Networks of Statisticians (with discussions). (website, pdf (with-supplement), pdf (with-discussions), data and code)
  Journal of Business & Economic Statistics, 40(2), 469-485.
  

Community detection:

• Jin, J., Ke, Z. and Luo, S. (2022).
  Improvements on SCORE, Especially for Weak Signals. (website, pdf, code)
  Sankhya A, 84(1), 127-162.
  
• Jiang, Y. and Ke, Z. (2023).
  Semi-supervised Community Detection via Structural Similarity Metrics. (arXiv, pdf, website)
  11th International Conference on Learning Representations (ICLR 2023).
  

Mixed membership estimation:

• Jin, J., Ke, Z. and Luo, S. (2024).
  Mixed Membership Estimation for Social Networks. (website, arXiv, pdf, supplement, code)
  (An old title: Estimating Network Memberships by Simplex Vertex Hunting.)
  Journal of Econometrics, 239(2), 105369.
  
• Ke, Z. and Wang, J. (2024).
  Optimal Network Membership Estimation under Severe Degree Heterogeneity. (arXiv, pdf)
  Journal of the American Statistical Association (minor revision)
  

Network inference via cycle counts:

• Jin, J., Ke, Z. and Luo, S. (2021).
  Optimal Adaptivity of Signed-Polygon Statistics for Network Testing. (website, pdf, supplement)
  Annals of Statistics, 49(6), 3408-3433.
  
• Jin, J., Ke, Z., Luo, S. and Wang, M. (2023).
  Optimal Estimation of the Number of Network Communities. (website, arXiv, pdf)
  Journal of the American Statistical Association, 118(543), 2101-2116.
  
• Cammarata, L. and Ke, Z. (2023).
  Power Enhancement and Phase Transitions for Global Testing of the Mixed Membership Stochastic Block Model. (website, arXiv, pdf, supplement, code)
  Bernoulli, 29(3), 1741-1763.
  
• Jin, J., Ke, Z. and Luo, S. (2018).
  Network Global Testing by Counting Graphlets. (website, pdf, supplement)
  35th International Conference on Machine Learning (ICML 2018).
  
• Jin, J., Ke, Z., Turner, P. and Zhang, A. (2023).
  Phase Transition for Detecting a Small Community in a Large Network. (arXiv, pdf, website)
  11th International Conference on Learning Representations (ICLR 2023).
  
• Jin, J., Ke, Z. and Liang, J. (2021).
  Sharp Impossibility Results for Hyper-graph Testing. (website, pdf, supplement)
  Advances in Neural Information Processing Systems (NeurIPS 2021).