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M. Grossglauser

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#machine learning Preprint Sep 2026

Hierarchical Clustering Can Jointly Satisfy Richness, Consistency, and Scale Invariance

This paper explicitly construct several admissible methods, including methods based on well-separated clusters and a non-binary version of single linkage, and shows that, in contrast to the flat clustering setting, the hierarchical analog of these axioms are jointly satisfiable.

Daichi Kuroda, Maximilien Dreveton, M. Grossglauser et al. · 0 citations