Patil, Pratik

10 publications

ECCV 2024 A Framework for Efficient Model Evaluation Through Stratification, Sampling, and Estimation Riccardo Fogliato, Pratik Patil, Mathew Monfort, Pietro Perona

ICLR 2024 Asymptotically Free Sketched Ridge Ensembles: Risks, Cross-Validation, and Tuning Pratik Patil, Daniel LeJeune

AISTATS 2024 Failures and Successes of Cross-Validation for Early-Stopped Gradient Descent Pratik Patil, Yuchen Wu, Ryan Tibshirani

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

ICML 2024 Optimal Ridge Regularization for Out-of-Distribution Prediction Pratik Patil, Jin-Hong Du, Ryan Tibshirani

JMLR 2023 Bagging in Overparameterized Learning: Risk Characterization and Risk Monotonization Pratik Patil, Jin-Hong Du, Arun Kumar Kuchibhotla

NeurIPS 2023 Generalized Equivalences Between Subsampling and Ridge Regularization Pratik Patil, Jin-Hong Du

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

AISTATS 2022 Estimating Functionals of the Out-of-Sample Error Distribution in High-Dimensional Ridge Regression Pratik Patil, Alessandro Rinaldo, Ryan Tibshirani

AISTATS 2021 Uniform Consistency of Cross-Validation Estimators for High-Dimensional Ridge Regression Pratik Patil, Yuting Wei, Alessandro Rinaldo, Ryan Tibshirani