Research map / Graph learning / Graph algorithms and clustering
A Convex Relaxation for Multi-Graph Matching
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use more graphs jointly in the matching problem | MP · C. elegans | precision | Helped |
| Use more graphs jointly in the matching problem | MP · C. elegans | recall | Helped |
| Add higher-order tightening to the relaxation (ablation) | MP · Synthetic complete | precision | No clear effect |
| Add higher-order tightening to the relaxation (ablation) | MP · Synthetic density, deform, and outlier | precision | Helped |
| Explicitly account for outliers in the matching formulation | MP · Synthetic outlier | precision | Helped |
| Use MP-T rather than competing methods | CMU house and hotel · CMU House & Hotel outlier | precision | Helped |
| Use MP-T rather than competing methods | CMU house and hotel · CMU House & Hotel outlier | recall | Helped |
Closest papers by meaning
- A Study of Lagrangean Decompositions and Dual Ascent Solvers for Graph Matching (CVPR 2017 · similarity 0.90)
- Learning Partial Graph Matching via Optimal Partial Transport (ICLR 2025 · similarity 0.88)
- Towards Optimizing Large-Scale Multi-Graph Matching in Bioimaging (CVPR 2025 · similarity 0.88)
- Graph Alignment via Birkhoff Relaxation (NeurIPS 2025 · similarity 0.86)
- Discrete Cycle-Consistency Based Unsupervised Deep Graph Matching (AAAI 2024 · similarity 0.86)
- Multi-Shape Matching with Cycle Consistency Basis via Functional Maps (AAAI 2025 · similarity 0.86)
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