Fiber product homotopy method for multiparameter eigenvalue problems. - Jose Israel Rodriguez; Jin-Hong Du; Yiling You; Lek-Heng Lim (Numerische Mathematik, 2021)

Subsample Ridge Ensembles: Equivalences and Generalized Cross-Validation. - Jin-Hong Du; Pratik Patil; Arun K. Kuchibhotla (ICML, 2023)

Generalized equivalences between subsampling and ridge regularization. - Pratik Patil; Jin-Hong Du (NeurIPS, 2023)

Simultaneous inference for generalized linear models with unmeasured confounders. - Jin-Hong Du; Larry A. Wasserman; Kathryn Roeder (CoRR, 2023)

Bagging in overparameterized learning: Risk characterization and risk monotonization. - Pratik Patil; Jin-Hong Du; Arun Kumar Kuchibhotla (J. Mach. Learn. Res., 2023)

Optimal Ridge Regularization for Out-of-Distribution Prediction. - Pratik Patil; Jin-Hong Du; Ryan J. Tibshirani (ICML, 2024)

Implicit Regularization Paths of Weighted Neural Representations. - Jin-Hong Du; Pratik Patil (NeurIPS, 2024)

Network-based Neighborhood regression. - Yaoming Zhen; Jin-Hong Du (CoRR, 2024)

Distance-Preserving Generative Modeling of Spatial Transcriptomics. - Wenbin Zhou; Jin-Hong Du (CoRR, 2024)

Revisiting Optimism and Model Complexity in the Wake of Overparameterized Machine Learning. - Pratik Patil; Jin-Hong Du; Ryan J. Tibshirani (CoRR, 2024)

Assumption-Lean Post-Integrated Inference with Negative Control Outcomes. - Jin-Hong Du; Kathryn Roeder; Larry A. Wasserman (CoRR, 2024)

Extrapolated Cross-Validation for Randomized Ensembles. - Jin-Hong Du; Pratik Patil; Kathryn Roeder; Arun Kumar Kuchibhotla (J. Comput. Graph. Stat., 2024)

Disentangled Feature Importance. - Jin-Hong Du; Kathryn Roeder; Larry A. Wasserman (CoRR, 2025)