HAL (France)
open access
SOS-SDP: An Exact Solver for Minimum Sum-of-Squares Clustering
The minimum sum-of-squares clustering problem (MSSC) consists of partitioning n observations into k clusters in order to minimize the sum of squared distances from the points to the centroid of their cluster. In this paper, we propose an exact algorithm for the MSSC problem based on the branch-and-b
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-Based Dimensionality Reduction by Nonparametric Distributional Screening#974935
- Revealed Social Networks#665469
- Revealed Social Networks#663969
- An Overview of Minimum Convex Cover and Maximum Hidden Set#180512
- An Overview of Minimum Convex Cover and Maximum Hidden Set#179650
Record · ID 1312404
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