Weijie Su

27 catalog papers. Identity-linked publications and additional name matches are distinguished below.

ORCID: 0000-0003-1787-1219

Department of Statistics and Data Science, University of Pennsylvania

Publications

Do large language models (really) need statistical foundations? — The Annals of Applied Statistics 2026
Robust detection of watermarks for large language models under human edits — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2026
You Are the Best Reviewer of Your Own Papers: The Isotonic Mechanism — Operations Research 2026
A statistical framework of watermarks for large language models: Pivot, detection efficiency and optimal rules — The Annals of Statistics 2025
Isotonic mechanism for exponential family estimation in machine learning peer review — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2025
On the Algorithmic Bias of Aligning Large Language Models with RLHF: Preference Collapse and Matching Regularization — Journal of the American Statistical Association 2025
Precise High-Dimensional Asymptotics for Quantifying Heterogeneous Transfers — Journal of Machine Learning Research 2025 (name-matched, not ORCID-linked)
Debiasing Watermarks for Large Language Models via Maximal Coupling — Journal of the American Statistical Association 2025
Characterizing the SLOPE trade-off: A variational perspective and the Donoho–Tanner limit — The Annals of Statistics 2023
A power analysis for model-X knockoffs with ℓp-regularized statistics — The Annals of Statistics 2023
HiGrad: Uncertainty Quantification for Online Learning and Stochastic Approximation — Journal of Machine Learning Research 2023 (name-matched, not ORCID-linked)
On Learning Rates and SchrÃ¶dinger Operators — Journal of Machine Learning Research 2023 (name-matched, not ORCID-linked)
Minimax Estimation for Personalized Federated Learning: An Alternative between FedAvg and Local Training? — Journal of Machine Learning Research 2023 (name-matched, not ORCID-linked)
Benign Overfitting and Noisy Features — Journal of the American Statistical Association 2023
Gaussian differential privacy — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2022
Authors’ reply to the Discussion of ‘Gaussian Differential Privacy’ by Donget al. — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2022
Detecting multiple replicating signals using adaptive filtering procedures — The Annals of Statistics 2022
Group SLOPE – Adaptive Selection of Groups of Predictors — Journal of the American Statistical Association 2019
Statistical inference for the population landscape via moment-adjusted stochastic gradients — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2019
Multiple Testing When Manyp-Values are Uniformly Conservative, with Application to Testing Qualitative Interaction in Educational Interventions — Journal of the American Statistical Association 2019
When is the first spurious variable selected by sequential regression procedures? — Biometrika 2018
False discoveries occur early on the Lasso path — The Annals of Statistics 2017
A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights — Journal of Machine Learning Research 2016 (name-matched, not ORCID-linked)
SLOPE is adaptive to unknown sparsity and asymptotically minimax — The Annals of Statistics 2016
SLOPE—Adaptive variable selection via convex optimization — The Annals of Applied Statistics 2015
The ICML 2023 Ranking Experiment: Examining Author Self-Assessment in ML/AI Peer Review — Journal of the American Statistical Association
Edgeworth Accountant: An Analytical Approach to Differential Privacy Composition — Journal of the American Statistical Association