A condition-number principle shows that small suboptimality in admissible prototype clustering objectives implies small misclassification error when the condition number is low, with phase transitions for exact recovery.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
other 1
citation-polarity summary
fields
stat.ML 1years
2026 1verdicts
UNVERDICTED 1roles
other 1polarities
unclear 1representative citing papers
citing papers explorer
-
The Condition-Number Principle for Prototype Clustering
A condition-number principle shows that small suboptimality in admissible prototype clustering objectives implies small misclassification error when the condition number is low, with phase transitions for exact recovery.