Research map / Learning theory and algorithms / Clustering
Adaptive Clustering through Semidefinite Programming
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add the bias-correction term to the semidefinite clustering estimator | Semidefinite clustering · High-dimensional clustering | separating rate: leading rate: γ²/m -> smaller than σ² √((K + log n)r*/m) | Helped |
| Use the corrected estimator rather than the compared classical clustering methods | Simulated Gaussian clustering · Scenario S1 | split-join error | Helped |
| Use the corrected estimator rather than the compared classical clustering methods | Simulated Gaussian clustering · Scenario S2 | split-join error | Helped |
| Remove the bias-correction term (ablation) | Semidefinite clustering · High-dimensional clustering | separating rate: γ²/m | Hurt |
| Use the corrected estimator instead of K-means | Simulated Gaussian clustering · Scenario S2 | split-join error | Mixed |
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