Research map / Learning theory and algorithms / Combinatorial and search optimization
Discovering Interpretable Data-to-Sequence Generators
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use CONSEQUENCE instead of DATS | Event-sequence prediction · Production | NLS: 0.35 -> 0.42 | Helped |
| Use CONSEQUENCE instead of LSTM | Event-sequence prediction · Sepsis | NLS: 0.51 -> 0.58 | Helped |
| Use CONSEQUENCE instead of LSTM | Event-sequence prediction · Rolling Mill | NLS: 0.99 -> 0.94 | Hurt |
| Use CONSEQUENCE instead of POSCL | Event-sequence prediction · Software | NLS: 0.69 -> 0.84 | Helped |
| Replace GERD with CANTMINERPB for rule learning (ablation) | CONSEQUENCE on synthetic data · Synthetic data with varying numbers of attributes | Training time | Hurt |
| Replace GERD with CLASSY for rule learning (ablation) | CONSEQUENCE on synthetic data · Synthetic data with varying numbers of attributes | Number of condition terms | Hurt |
| Train on larger subsets of Rolling Mill data | CONSEQUENCE · Rolling Mill | NLS | No clear effect |
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