arxivcs.LGcs.AIstat.ML2026-06-29
What Drives the Inlier-Memorization Effect? A Theory of Outlier Detection via Early Training Dynamics
Outlier detection (OD) aims to identify anomalous instances by learning the underlying structure of normal data (inliers), and is particularly challenging in fully unsupervised settings where no information about anomalies is available during training. Recent advances have levera…