Research map / Label-efficient and robust learning / Recognition and long-tail
Partial Multi-Label Learning via Credible Label Elicitation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| credible label elicitation + pairwise ranking (PARTICLE-VLS) vs PML-LC | partial multi-label learning · 37 data sets, 5 metrics | significant wins: 90.2% | Helped |
| PARTICLE-MAP vs PML-FP | partial multi-label learning · 37 data sets, 5 metrics | significant wins: 82.1% | Helped |
| PARTICLE vs CLR | partial multi-label learning · music style | ranking loss | Hurt |
| vary credible label threshold thr from 1 down to 0.5 (ablation) | PARTICLE-VLS · PML data sets | average precision | No clear effect |
Closest papers by meaning
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- Distilling Reliable Knowledge for Instance-Dependent Partial Label Learning (AAAI 2024 · similarity 0.85)
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