Publications

2026

  1. When Does Subspace Direction Matter for LoRA? Regime Analysis of the Magnitude Principle in Few-Shot Adaptation
    Nischal Subedi, Cencheng Shen, and Peng Zhao
    In Advances in Neural Information Processing Systems (NeurIPS), 2026
    Accepted
  2. Beyond Negative-Ridge Endpoints: Mixed-Sign Spectral Regularization via Negative-Shifted Gradient Descent
    Peng Zhao
    arXiv preprint arXiv:2607.22474, 2026
    arXiv alphaXiv Blog Code
  3. De-floored Principal Component Regression: When Rank Selection Alone Is Insufficient for Prediction
    Peng Zhao
    arXiv preprint arXiv:2607.16638, 2026
    arXiv alphaXiv Blog Code
  4. An Approximate Bayesian Approach to Covariate-dependent Graphical Modeling
    Sutanoy Dasgupta, Peng Zhao, Jacob Helwig, Prasenjit Ghosh, Debdeep Pati, and Bani K. Mallick
    Bernoulli, 2026
    Accepted
    arXiv

2025

  1. Robust High-Dimensional Covariate-Assisted Network Modeling
    Peng Zhao and Yabo Niu
    arXiv preprint arXiv:2505.02986, 2025
    arXiv

2024

  1. Tail-adaptive Bayesian Shrinkage
    Seonghyun Lee, Peng Zhao, Debdeep Pati, and Bani K. Mallick
    Electronic Journal of Statistics, 2024
    DOI arXiv HTML
  2. Structured Optimal Variational Inference for Dynamic Latent Space Models
    Peng Zhao, Anirban Bhattacharya, Debdeep Pati, and Bani K. Mallick
    Journal of Machine Learning Research, 2024
    arXiv HTML
  3. covdepGE: A Covariate-dependent Approach to Gaussian Graphical Modeling in R
    Jacob Helwig, Sutanoy Dasgupta, Peng Zhao, Bani K. Mallick, and Debdeep Pati
    ACM Transactions on Mathematical Software, 2024
    HTML
  4. An Active Learning-based Approach for Hosting Capacity Analysis in Distribution Systems
    Kyung Lee, Peng Zhao, Anirban Bhattacharya, Bani K. Mallick, and Le Xie
    IEEE Transactions on Smart Grid, 2024
    DOI arXiv HTML
  5. Query-decision Regression Between Shortest Path and Minimum Steiner Tree
    Guangmo Tong, Peng Zhao, and Meisam Samizadeh
    In Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2024
    arXiv HTML

2023

  1. Spatial Clustering Regression of Count Value Data via Bayesian Mixture of Finite Mixtures
    Peng Zhao, Hou-Cheng Yang, Dipak K. Dey, and Guanyu Hu
    In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
    DOI arXiv HTML

2022

  1. High-dimensional Linear Regression via Implicit Regularization
    Peng Zhao, Yun Yang, and Qiao-Chu He
    Biometrika, 2022
    DOI arXiv HTML
  2. Factorized Fusion Shrinkage for Dynamic Relational Data
    Peng Zhao, Anirban Bhattacharya, Debdeep Pati, and Bani K. Mallick
    arXiv preprint arXiv:2210.00091, 2022
    arXiv

2021

  1. Approximate Bayesian Estimation with Subsampled Logistic Regression in Big Data Settings
    Peng Zhao and Guanyu Hu
    In 2021 IEEE International Conference on Big Data, 2021
    HTML
  2. Discussion of Multilevel Linear Models, Gibbs Samplers and Multigrid Decompositions
    Peng Zhao, Hou-Cheng Yang, Dipak K. Dey, and Guanyu Hu
    Bayesian Analysis, 2021