Research map / Learning theory and algorithms / Prediction and decision losses
An Improved Algorithm for Learning to Perform Exception-Tolerant Abduction
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use Low Deg. partial red-blue set cover instead of Tolerant Elimination | exception-tolerant k-DNF abduction · Noisy planted k-DNF | error rate: 5.985% -> 5.996% (1-DNF); 5.915% -> 5.847% (2-DNF) | No clear effect |
| use Low Deg. partial cover instead of Tolerant Elimination | exception-tolerant k-DNF abduction · Random linear threshold rules | error rate: ≈50% -> significantly lower | Helped |
| use Low Deg. partial cover instead of naive greedy baseline (ablation) | exception-tolerant k-DNF abduction · Random linear threshold rules | error rate | Helped |
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