Research map / Label-efficient and robust learning / OOD and anomaly detection
Adaptive Double-Exploration Tradeoff for Outlier Detection
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use ADE instead of RR and WRR | threshold bandit outlier detection · synthetic, n from 200 to 1000 | number of samples | Helped |
| use ADE instead of RR and WRR with small n | threshold bandit outlier detection · synthetic, n = 100 | number of samples | Hurt |
| increase number of arms n (ablation) | ADE, RR, WRR · synthetic | number of samples | Hurt |
| increase minimum gap Delta_min (ablation) | ADE, RR, WRR · synthetic, n = 900 | number of samples | Helped |
| use ADE instead of RR and WRR | threshold bandit outlier detection · HyunCatherines, k = 2 and 3 | number of samples | Helped |
| increase k from 2 to 3 (ablation) | ADE, RR, WRR · HyunCatherines | number of samples | Helped |
| WRR instead of RR | round-robin sampling · synthetic, n = 100 | number of samples | Helped |
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