Anomaly-Free Self-Optimization via AUC Bounds

arXiv:2609.27362 · cs.LG, eess.AS · Submitted 2026-09-23 · Read on arXiv

cs.LG, eess.AS

Submitted: 2026-09-23

Updated: 2026-09-23

Terminology

• AUC — 38× in this paper · explained in 2 episodes
• Aggregation — 6× in this paper · explained in 1 episode
• Embeddings — 5× in this paper · explained in 2 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• Ensemble Learning — 3× in this paper · explained in 2 episodes
• Generalization — 3× in this paper · explained in 13 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Domain Shift — 2× in this paper · explained in 4 episodes
• Generative AI — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Bayesian Optimization — 1× in this paper · explained in 3 episodes
• Ensemble Approach — 1× in this paper · explained in 3 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Meta-learning — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Temporal Pooling Strategies for Training-Free Anomalous Sound Detection with Self-Supervised Audio Embeddings
• Can We Predict Anomaly Detection Performance from Embedding-Space Geometry?

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