When majority rules, minority loses: bias amplification of gradient descent
DGX agentarXiv:2505.13122v3 Announce Type: replace-cross Abstract: Despite growing empirical evidence of bias amplification in machine learning, its theoretical foundations remain poorly understood. We develop