Research map / Learning theory and algorithms / Clustering
Optimal LP Rounding and Linear-Time Approximation Algorithms for Clustering Edge-Colored Hypergraphs
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use Hybrid instead of MatchColoring | MinECC on Trivago · Trivago | mistakes: 77606 -> 65192 | Helped |
| use Hybrid instead of MatchColoring | MinECC on Trivago · Trivago | Acc: 0.70 -> 0.78 | Helped |
| use Hybrid instead of MajorityVote | MinECC on Trivago · Trivago | mistakes: 67941 -> 65192 | Helped |
| use Hybrid instead of MajorityVote | MinECC on Trivago · Trivago | Run: 0.11 -> 0.23 | Hurt |
| use PittColoring instead of MajorityVote | MinECC on Walmart · Walmart | ratio to LP lower bound: 1.2 -> 1.13 | Helped |
Closest papers by meaning
- Edge-Colored Clustering in Hypergraphs: Beyond Minimizing Unsatisfied Edges (ICML 2025 · similarity 0.95)
- Improved Algorithms for Overlapping and Robust Clustering of Edge-Colored Hypergraphs: An LP-Based Combinatorial Approach (NeurIPS 2025 · similarity 0.94)
- Improved Approximation Algorithms for Chromatic and Pseudometric-Weighted Correlation Clustering (NeurIPS 2025 · similarity 0.89)
- Dynamic Correlation Clustering in Sublinear Update Time (ICML 2024 · similarity 0.86)
- Combinatorial Approximations for Cluster Deletion: Simpler, Faster, and Better (ICML 2024 · similarity 0.86)
- Optimal Graph Clustering without Edge Density Signals (NeurIPS 2025 · similarity 0.85)
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