Research

2024

  1. Towards the Theory of Unsupervised Federated Learning: Non-asymptotic Analysis of Federated EM Algorithms
    Ye Tian, Haolei Weng, and Yang Feng
    International Conference on Machine Learning, 2024
  2. Variable Selection in Ultra-high Dimensional Feature Space for the Cox Model with Interval-Censored Data
    Daewoo Pak, Jianrui Zhang, Di Wu, Haolei Weng, and Chenxi Li
    2024
  3. A note on the minimax risk of sparse linear regression
    Yilin Guo, Shubhangi Ghosh, Haolei Weng, and Arian Maleki
    2024

2023

  1. Spectral clustering via adaptive layer aggregation for multi-layer networks
    Sihan Huang, Haolei Weng, and Yang Feng
    Journal of Computational and Graphical Statistics, 2023
  2. Variable Selection in Latent Regression IRT Models via Knockoffs: An Application to International Large-scale Assessment in Education
    Zilong Xie, Yunxiao Chen, Matthias von Davier, and Haolei Weng
    Journal of the Royal Statistical Society: Series A, 2023
  3. Signal-to-noise ratio aware minimaxity and higher-order asymptotics
    Yilin Guo, Haolei Weng, and Arian Maleki
    IEEE Transactions on Information Theory, 2023
  4. Post-Selection Inference for the Cox Model with Interval-Censored Data
    Jianrui Zhang, Chenxi Li, and Haolei Weng
    2023

2022

  1. Does SLOPE outperform bridge regression?
    Shuaiwen Wang, Haolei Weng, and Arian Maleki
    Information and Inference: A Journal of the IMA, 2022
  2. Community detection with nodal information: Likelihood and its variational approximation
    Haolei Weng, and Yang Feng
    Stat, 2022
  3. Discussion of “Cocitation and Coauthorship Networks of Statisticians”
    Haolei Weng, and Yang Feng
    Journal of Business & Economic Statistics, 2022
  4. Unsupervised Multi-task and Transfer Learning on Gaussian Mixture Models
    Ye Tian, Haolei Weng, and Yang Feng
    2022

2021

  1. Optimal estimation of functionals of high-dimensional mean and covariance matrix
    Jianqing Fan, Haolei Weng, and Yifeng Zhou
    2021

2020

  1. Low noise sensitivity analysis of ℓq-minimization in oversampled systems
    Haolei Weng, and Arian Maleki
    Information and Inference: A Journal of the IMA, 2020
  2. On the estimation of correlation in a binary sequence model
    Haolei Weng, and Yang Feng
    Journal of Statistical Planning and Inference, 2020
  3. Computing the degrees of freedom of rank-regularized estimators and cousins
    Rahul Mazumder, and Haolei Weng
    Electronic Journal of Statistics, 2020
  4. Matrix completion with nonconvex regularization: spectral operators and scalable algorithms
    Rahul Mazumder, Diego Saldana, and Haolei Weng
    Statistics and Computing, 2020
  5. Which bridge estimator is the best for variable selection?
    Shuaiwen Wang, Haolei Weng, and Arian Maleki
    The Annals of Statistics, 2020

2019

  1. Regularization after retention in ultrahigh dimensional linear regression models
    Haolei Weng, Yang Feng, and Xingye Qiao
    Statistica Sinica, 2019

2018

  1. Overcoming the limitations of phase transition by higher order analysis of regularization techniques
    Haolei Weng, Arian Maleki, and Le Zheng
    The Annals of Statistics, 2018

2017

  1. Does ℓp-minimization outperform ℓ1-minimization?
    Le Zheng, Arian Maleki, Haolei Weng, Xiaodong Wang, and Teng Long
    IEEE Transactions on Information Theory, 2017

2016

  1. Phase transition and noise sensitivity of ℓp-minimization for 0 ≤p ≤1
    Haolei Weng, Le Zheng, Arian Maleki, and Xiaodong Wang
    In 2016 IEEE International Symposium on Information Theory (ISIT), 2016