A Divide-and-Merge Methodology for Clustering
Summary: Divide-and-merge clustering: spectral top-down divide builds a tree of items; bottom-up merge efficiently finds optimal tree-respecting partitions for many objectives (k-means, min-diameter, min-sum, correlation). Applied to web meta-search and text data, competitive or superior to prior methods. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. David Cheng
- 2. Ravi Kannan
- 3. Santosh Vempala
- 4. Grant Wang
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