Research map / Label-efficient and robust learning / Recognition and long-tail
Online Metric Learning for Multi-Label Classification
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use OML instead of OSML-ELM | Online multi-label classification · Most benchmark datasets | F1 / Hamming Loss | Helped |
| Use OML instead of OLANSGD | Online multi-label classification · Most benchmark datasets | F1 / Hamming Loss | Helped |
| Learn a metric with OML instead of using Euclidean kNN | Online multi-label classification · All datasets except Cal500 under Hamming Loss | F1 / Hamming Loss | Helped |
| Learn a metric with OML instead of using Euclidean kNN | Online multi-label classification · Cal500 | Hamming Loss | No clear effect |
Closest papers by meaning
- T-MDML: Triplet-based Multiple Distance Metric Learning for Multi-Instance Multi-Label Classification with Label Correlation (AAAI 2025 · similarity 0.88)
- Consistent algorithms for multi-label classification with macro-at-$k$ metrics (ICLR 2024 · similarity 0.88)
- A General Online Algorithm for Optimizing Complex Performance Metrics (ICML 2024 · similarity 0.87)
- Implicit Relative Labeling-Importance Aware Multi-Label Metric Learning (AAAI 2025 · similarity 0.87)
- Generalization Analysis for Multi-Label Learning (ICML 2024 · similarity 0.85)
- Multi-Label Learning with Stronger Consistency Guarantees (NeurIPS 2024 · similarity 0.84)
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