Research map / Learning theory and algorithms / Clustering
Clustering with Same-Cluster Queries
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use same-cluster queries to recover a γ-margin clustering | Euclidean center-based clustering with γ > 1 · Euclidean center-based clustering with γ-margin, γ > 1 | computational complexity: NP hard -> probabilistic polynomial-time | Helped |
| Use same-cluster queries with the SSAC algorithm | Euclidean clustering instances with γ-margin, γ > 1 · Euclidean clustering instances with γ-margin, γ > 1 | query complexity: O(k^2\log k + k\log n) | Helped |
| Solve without access to query answers | Euclidean k-means · Euclidean k-means, k=Θ(n^ε), ε ∈ (0,1), γ-margin γ=√3.4 | computational complexity: NP-hard | Hurt |
| Use an oracle and at least Ω(log k + log n) queries | Efficient clustering algorithm · Euclidean k-means, k=Θ(n^ε), ε ∈ (0,1), γ-margin γ=√3.4 | query complexity: Ω(log k + log n) | Helped |
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