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.
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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.