Research map / Learning theory and algorithms / Clustering
Efficient Clustering Based On A Unified View Of $K$-means And Ratio-cut
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use k-sums (kNN-graph distance sum, linear time) instead of k-means | clustering · Face-94 | clustering accuracy: 0.722 -> 0.961 | Helped |
| Use k-sums instead of k-means | clustering · Olivetti | clustering accuracy: 0.462 -> 0.367 | Hurt |
| Use k-sums instead of k-means | clustering · Finger | clustering accuracy: 0.311 -> 0.395 | Mixed |
| Use k-sums instead of k-means | clustering · Grid-100w | running time (s): 3416.70 -> 221.50 | Helped |
| Use k-sums instead of k-means | clustering · CelebA | running time (s): 2.3E2 -> 31.2 | Helped |
| Use k-sums instead of k-means | clustering · CelebA | F1 score: 0.347 -> 0.464 | Helped |
| Use k-sums instead of k-means | clustering · CPLFW | F1 score: 0.477 -> 0.404 | Hurt |
| Use k-sums instead of k-means | clustering · Adience | F1 score: 0.614 -> 0.572 | Hurt |
| Use k-sums instead of k-means | clustering · PEAL | F1 score: 0.785 -> 0.871 | Helped |
Closest papers by meaning
- A Sampling-Based Approach for Efficient Clustering in Large Datasets (CVPR 2022 · similarity 0.91)
- A Tighter Analysis of Spectral Clustering, and Beyond (ICML 2022 · similarity 0.90)
- Simple, Scalable and Effective Clustering via One-Dimensional Projections (NeurIPS 2023 · similarity 0.90)
- Balanced Clustering via Exclusive Lasso: A Pragmatic Approach (AAAI 2018 · similarity 0.90)
- Efficient Constrained K-center Clustering with Background Knowledge (AAAI 2024 · similarity 0.88)
- Unified K-Means Clustering with Label-Guided Manifold Learning (ICML 2025 · similarity 0.88)
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