| A machine learning framework for stock selection XY Fu, JH Du, YF Guo, MW Liu, T Dong, XW Duan arXiv preprint arXiv:1806.01743, 2018 | 36 | 2018 |
| Increasing the energy efficiency of a data center based on machine learning Z Yang, J Du, Y Lin, Z Du, L Xia, Q Zhao, X Guan Journal of Industrial Ecology 26 (1), 323-335, 2022 | 28 | 2022 |
| Robust probabilistic modeling for single-cell multimodal mosaic integration and imputation via scVAEIT JH Du, Z Cai, K Roeder Proceedings of the National Academy of Sciences 119 (49), e2214414119, 2022 | 26 | 2022 |
| Joint trajectory inference for single-cell genomics using deep learning with a mixture prior JH Du, T Chen, M Gao, J Wang Proceedings of the National Academy of Sciences 121 (37), e2316256121, 2024 | 16* | 2024 |
| Predictive maintenance of vrla batteries in ups towards reliable data centers JX Tang, JH Du, Y Lin, QS Jia IFAC-PapersOnLine 53 (2), 13607-13612, 2020 | 16 | 2020 |
| Bagging in overparameterized learning: Risk characterization and risk monotonization P Patil, JH Du, AK Kuchibhotla Journal of Machine Learning Research 24 (319), 1--113, 2023 | 15 | 2023 |
| Fiber product homotopy method for multiparameter eigenvalue problems JI Rodriguez, JH Du, Y You, LH Lim Numerische Mathematik 148, 853-888, 2021 | 14 | 2021 |
| Subsample Ridge Ensembles: Equivalences and Generalized Cross-Validation JH Du, P Patil, AK Kuchibhotla Proceedings of the 40th International Conference on Machine Learning 202 …, 2023 | 12 | 2023 |
| High-dimensional portfolio selection with cardinality constraints JH Du, Y Guo, X Wang Journal of the American Statistical Association 118 (542), 779-791, 2023 | 12 | 2023 |
| Generalized equivalences between subsampling and ridge regularization P Patil, JH Du Thirty-seventh Conference on Neural Information Processing Systems, 2023 | 10 | 2023 |
| Corrected generalized cross-validation for finite ensembles of penalized estimators PC Bellec, JH Du, T Koriyama, P Patil, K Tan Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2024 | 5 | 2024 |
| Optimal Ridge Regularization for Out-of-Distribution Prediction P Patil, JH Du, RJ Tibshirani Forty-first International Conference on Machine Learning, 2024 | 5 | 2024 |
| Extrapolated cross-validation for randomized ensembles JH Du, P Patil, K Roeder, AK Kuchibhotla Journal of Computational and Graphical Statistics, 1-12, 2024 | 5 | 2024 |
| Causal inference for genomic data with multiple heterogeneous outcomes JH Du, Z Zeng, EH Kennedy, L Wasserman, K Roeder arXiv preprint arXiv:2404.09119, 2024 | 4 | 2024 |
| Simultaneous inference for generalized linear models with unmeasured confounders JH Du, L Wasserman, K Roeder arXiv preprint arXiv:2309.07261, 2023 | 3 | 2023 |
| Precise asymptotics of bagging regularized m-estimators T Koriyama, P Patil, JH Du, K Tan, PC Bellec arXiv preprint arXiv:2409.15252, 2024 | 2 | 2024 |
| Decoupling convolution network for characterizing the metastatic lymph nodes of breast cancer patients R Zeng, X Zhang, C Zheng, JH Du, Z Gao, W Jun, J Shen, Y Lu Medical Physics 48 (7), 3679-3690, 2021 | 2 | 2021 |
| Implicit Regularization Paths of Weighted Neural Representations JH Du, P Patil Thirty-eighth Conference on Neural Information Processing Systems, 2024 | 1 | 2024 |
| Assumption-Lean Post-Integrated Inference with Negative Control Outcomes JH Du, K Roeder, L Wasserman arXiv preprint arXiv:2410.04996, 2024 | | 2024 |
| Revisiting Optimism and Model Complexity in the Wake of Overparameterized Machine Learning P Patil, JH Du, RJ Tibshirani arXiv preprint arXiv:2410.01259, 2024 | | 2024 |
Pratik PatilUniversity of California BerkeleyVerified email at berkeley.edu