Research map / Learning theory and algorithms / Clustering
Fast Approximate Spectral Clustering for Dynamic Networks
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Reuse 50% of previously computed signals (ablation) | Dynamic CSC · SBM, n=1000, s=25, e=\frac16 | multiplicative k-means cost error: up to 3% of the SC cost | Hurt |
| Reuse more previously computed features (ablation) | Dynamic CSC · Dynamic SBM experiments | time: 25% | Helped |
| Use compressive spectral clustering instead of eigendecomposition-based spectral clustering | Spectral clustering · Dynamic SBM experiments as n increases | time | Helped |
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