A Theoretical Analysis of the Learning Dynamics under Class Imbalance

1 July 2022

Papers citing "A Theoretical Analysis of the Learning Dynamics under Class Imbalance"

8 / 8 papers shown

Title
When resampling/reweighting improves feature learning in imbalanced classification?: A toy-model study Tomoyuki Obuchi Toshiyuki Tanaka 64 0 0 09 Sep 2024
Restoring balance: principled under/oversampling of data for optimal classification Emanuele Loffredo Mauro Pastore Simona Cocco R. Monasson 45 9 0 15 May 2024
Heavy-Tailed Class Imbalance and Why Adam Outperforms Gradient Descent on Language Models Frederik Kunstner Robin Yadav Alan Milligan Mark Schmidt Alberto Bietti 46 26 0 29 Feb 2024
Can Continual Learning Improve Long-Tailed Recognition? Toward a Unified Framework Mahdiyar Molahasani Michael A. Greenspan Ali Etemad 24 2 0 23 Jun 2023
An Investigation of Why Overparameterization Exacerbates Spurious Correlations Shiori Sagawa Aditi Raghunathan Pang Wei Koh Percy Liang 152 372 0 09 May 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 344 4,230 0 23 Aug 2019
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark Schmidt 139 1,204 0 16 Aug 2016
SMOTE: Synthetic Minority Over-sampling Technique Nitesh Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 163 25,296 0 09 Jun 2011