principal component regression

Benign Overfitting in Out-of-Distribution Generalization of Linear Models ICLR 2025 Minimax Optimal Nonsmooth Nonparametric Regression via Fractional Laplacian Eigenmaps UAI 2025 On Model Identification and Out-of-Sample Prediction of PCR with Applications to Synthetic Controls JMLR 2025 Training Dynamics of In-Context Learning in Linear Attention ICML 2025 No Double Descent in Principal Component Regression: A High-Dimensional Analysis ICML 2024 Adaptive Principal Component Regression with Applications to Panel Data NeurIPS 2023 Errors-in-variables Fr\'echet Regression with Low-rank Covariate Approximation NeurIPS 2023 Interpolating Predictors in High-Dimensional Factor Regression JMLR 2022 Prediction Under Latent Factor Regression: Adaptive PCR, Interpolating Predictors and Beyond JMLR 2021 Principal Component Regression with Semirandom Observations via Matrix Completion AISTATS 2021 On Robustness of Principal Component Regression NeurIPS 2019 On the number of variables to use in principal component regression NeurIPS 2019 Principal Component Projection and Regression in Nearly Linear Time through Asymmetric SVRG NeurIPS 2019 Faster Principal Component Regression and Stable Matrix Chebyshev Approximation ICML 2017 One-shot learning and big data with n=2 NeurIPS 2013 Robust Sparse Principal Component Regression under the High Dimensional Elliptical Model NeurIPS 2013 Penalized Principal Component Regression on Graphs for Analysis of Subnetworks NeurIPS 2010 Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression NeurIPS 2007 Kernel Partial Least Squares Regression in Reproducing Kernel Hilbert Space JMLR 2001