Table of Contents
This repo contains code for reproducing results in the following papers:
| Codename | Paper | Links |
|---|---|---|
| bagging | Pratik Patil, Jin-Hong Du, and Arun Kumar Kuchibhotla. “Bagging in overparameterized learning: Risk characterization and risk monotonization.” Journal of Machine Learning Research (2023) | [JMLR] [arXiv] [Github] |
| ecv | Jin-Hong Du, Pratik Patil, Kathryn Roeder, and Arun Kumar Kuchibhotla, “Extrapolated cross-validation for randomized ensembles”. In: Journal of Computational and Graphical Statistics (2023) | [arXiv] [DOI] [Github] |
| gcv | Jin-Hong Du, Pratik Patil, and Arun Kumar Kuchibhotla. “Subsample Ridge Ensembles: Equivalences and Generalized Cross-Validation.” Proceedings of the 40th International Conference on Machine Learning (2023) | [PMLR] [arXiv] [Github] |
| cgcv | Pierre C. Bellec, Jin-Hong Du, Takuya Koriyama, Pratik Patil, and Kai Tan. “Corrected generalized cross-validation for finite ensembles of penalized estimators.” arXiv preprint arXiv:2310.01374 (2023) | [arXiv] [Github] |
| equiv | Pratik Patil and Jin-Hong Du. “Generalized equivalences between subsampling and ridge regularization.” Thirty-seventh Conference on Neural Information Processing Systems (2023) | [arXiv] [Github] |
| weighted-neural | Jin-Hong Du and Pratik Patil. “Implicit Regularization Paths of Weighted Neural Representations.” (2024) | [arXiv] |
| subagging-asymptotics | Takuya Koriyama, Pratik Patil, Jin-Hong Du, Kai Tan, and Pierre C. Bellec. “Precise Asymptotics of Bagging Regularized M-estimators.” (2024) | [arXiv] |