Research map / Label-efficient and robust learning / Recognition and long-tail
Consensus Guided Unsupervised Feature Selection
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| select features guided by consensus-clustering pseudo labels (CGUFS) instead of NDFS | unsupervised feature selection · Yale | NMI: 0.4531 -> 0.6118 | Helped |
| CGUFS instead of NDFS | unsupervised feature selection · tr11 | NMI: 0.1426 -> 0.2514 | Helped |
| CGUFS instead of MCFS | unsupervised feature selection · ORL | NMI: 0.7653 -> 0.7889 | Helped |
| CGUFS instead of NDFS | unsupervised feature selection · MNIST | NMI: 0.4686 -> 0.4665 | No clear effect |
| CGUFS (selected features) instead of using all features (Baseline) | clustering · COIL20 | NMI: 0.7675 -> 0.7555 | Hurt |
| CGUFS instead of all features (Baseline) | clustering · ORL | NMI: 0.4078 -> 0.7889 | Helped |
| generate basic partitions with random feature selection instead of random parameter selection (ablation) | CGUFS · MNIST | NMI | Hurt |
| generate basic partitions with random feature selection instead of random parameter selection (ablation) | CGUFS · COIL20 | NMI | No clear effect |
| increase alpha and beta (consensus and l2,1 sparsity weights) (ablation) | CGUFS · ORL, oh15 | NMI | Helped |
Closest papers by meaning
- Preserving Ordinal Consensus: Towards Feature Selection for Unlabeled Data (AAAI 2020 · similarity 0.90)
- Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data (NeurIPS 2024 · similarity 0.85)
- Embedded Feature Selection on Graph-Based Multi-View Clustering (AAAI 2024 · similarity 0.84)
- ROLL: Robust Noisy Pseudo-label Learning for Multi-View Clustering with Noisy Correspondence (CVPR 2025 · similarity 0.84)
- Robust Consensus Anchor Learning for Efficient Multi-view Subspace Clustering (ICML 2025 · similarity 0.84)
- SAND: One-Shot Feature Selection with Additive Noise Distortion (ICML 2025 · similarity 0.84)
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