arXiv (All)
open access
Competitive Random-Order Correlation k-Clustering
Correlation clustering has been extensively studied over the last two decades in many different computational models owing to its wide-ranging practical applications. The goal is to compute a partition of the vertex set such that the total number of disagreements, i.e. the sum of edges between clust
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Cluster-Aware Matching via Laplacian Optimal Transport#381722
- Polychromatic Partitions, Kingman Theory, and Ewens Sampling Formula#793367
- Polychromatic Partitions, Kingman Theory, and Ewens Sampling Formula#789363
- Parameterized and Streaming Algorithms for Euclidean Fair $k$-Center Clustering#973965
- Ensemble KF with Statistical Orthogonality#641063
Record · ID 1130135
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive