Research map / Graph learning / Graph algorithms and clustering
Priori Anchor Labels Supervised Scalable Multi-View Bipartite Graph Clustering
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add prior anchor graph regularization (PAGG) using prior anchor labels (PAL) (ablation) | SMGC (compared with CAG, which sets β = 0) · Caltech101-20 | ACC: 0.6547 -> 0.6697 | Helped |
| Add prior anchor graph regularization (PAGG) using prior anchor labels (PAL) (ablation) | SMGC (compared with CAG, which sets β = 0) · CCV | ACC: 0.2399 -> 0.2368 | Hurt |
| Add prior anchor graph regularization (PAGG) using prior anchor labels (PAL) (ablation) | SMGC (compared with CAG, which sets β = 0) · Caltech101-all | ACC: 0.3015 -> 0.3584 | Helped |
| Add prior anchor graph regularization (PAGG) using prior anchor labels (PAL) (ablation) | SMGC (compared with CAG, which sets β = 0) · SUNRGBD | ACC: 0.2392 -> 0.2462 | Helped |
| Add prior anchor graph regularization (PAGG) using prior anchor labels (PAL) (ablation) | SMGC (compared with CAG, which sets β = 0) · NUSWIDEOBJ | ACC: 0.1946 -> 0.2210 | Helped |
| Add prior anchor graph regularization (PAGG) using prior anchor labels (PAL) (ablation) | SMGC (compared with CAG, which sets β = 0) · AwA | ACC: 0.0919 -> 0.1006 | Helped |
| Set the PAGG weight β to 0 (ablation) | SMGC on multiple benchmark datasets · UCI-DIGIT | anchor distribution uniformity | Hurt |
| Vary the number of anchors (ablation) | SMGC on Caltech101-all, SUNRGBD, NUSWIDEOBJ, and AwA · multiple datasets | ACC | Mixed |
Closest papers by meaning
- Learn from View Correlation: An Anchor Enhancement Strategy for Multi-view Clustering (CVPR 2024 · similarity 0.91)
- Learning Cluster-Wise Anchors for Multi-View Clustering (AAAI 2024 · similarity 0.91)
- Max-Mahalanobis Anchors Guidance for Multi-View Clustering (AAAI 2025 · similarity 0.91)
- Anchor Learning with Potential Cluster Constraints for Multi-view Clustering (AAAI 2025 · similarity 0.90)
- A Non-parametric Graph Clustering Framework for Multi-View Data (AAAI 2024 · similarity 0.90)
- From Spectrum-free towards Baseline-view-free: Double-track Proximity Driven Multi-view Clustering (ICML 2025 · similarity 0.90)
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