Sharp analysis of out-of-distribution error for "importance-weighted" estimators in the overparameterized regime

10 May 2024

Papers citing "Sharp analysis of out-of-distribution error for "importance-weighted" estimators in the overparameterized regime"

10 / 10 papers shown

Title
General Loss Functions Lead to (Approximate) Interpolation in High Dimensions Kuo-Wei Lai Vidya Muthukumar 49 5 0 13 Mar 2023
AutoBalance: Optimized Loss Functions for Imbalanced Data Mingchen Li Xuechen Zhang Christos Thrampoulidis Jiasi Chen Samet Oymak 38 67 0 04 Jan 2022
Covariate Shift in High-Dimensional Random Feature Regression Nilesh Tripuraneni Ben Adlam Jeffrey Pennington OOD 35 24 0 16 Nov 2021
Long-tail learning via logit adjustment A. Menon Sadeep Jayasumana A. S. Rawat Himanshu Jain Andreas Veit Sanjiv Kumar 109 707 0 14 Jul 2020
Classification vs regression in overparameterized regimes: Does the loss function matter? Vidya Muthukumar Adhyyan Narang Vignesh Subramanian M. Belkin Daniel J. Hsu A. Sahai 78 151 0 16 May 2020
An Investigation of Why Overparameterization Exacerbates Spurious Correlations Shiori Sagawa Aditi Raghunathan Pang Wei Koh Percy Liang 182 379 0 09 May 2020
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization Shiori Sagawa Pang Wei Koh Tatsunori B. Hashimoto Percy Liang OOD 85 1,236 0 20 Nov 2019
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss Kaidi Cao Colin Wei Adrien Gaidon Nikos Arechiga Tengyu Ma 107 1,594 0 18 Jun 2019
Confounding variables can degrade generalization performance of radiological deep learning models J. Zech Marcus A. Badgeley Manway Liu A. Costa J. Titano Eric K. Oermann OOD 83 1,173 0 02 Jul 2018
Marginal Singularity, and the Benefits of Labels in Covariate-Shift Samory Kpotufe Guillaume Martinet 127 95 0 05 Mar 2018