ordinary least square

Robustness Auditing for Linear Regression: To Singularity and Beyond ICLR 2025 Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares Extended Abstract COLT 2024 Minimax Linear Regression under the Quantile Risk COLT 2024 DARE-GRAM: Unsupervised Domain Adaptation Regression by Aligning Inverse Gram Matrices CVPR 2023 Provably Auditing Ordinary Least Squares in Low Dimensions ICLR 2023 Foolish Crowds Support Benign Overfitting JMLR 2022 Time Varying Regression with Hidden Linear Dynamics L4DC 2022 The Implicit Regularization of Ordinary Least Squares Ensembles AISTATS 2020 Scalable Approximations for Generalized Linear Problems JMLR 2019 Cheap Checking for Cloud Computing: Statistical Analysis via Annotated Data Streams AISTATS 2018 Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification COLT 2018 Differentially Private Ordinary Least Squares ICML 2017 No penalty no tears: Least squares in high-dimensional linear models ICML 2016 Alternating Minimization for Regression Problems with Vector-valued Outputs NeurIPS 2015 Elementary Estimators for High-Dimensional Linear Regression ICML 2014 A Risk Comparison of Ordinary Least Squares vs Ridge Regression JMLR 2013 Random Design Analysis of Ridge Regression COLT 2012 Directed Regression NeurIPS 2009