A self-guided, label-free hyperparameter tuning method for subspace clustering that splits hyperparameter intervals based on agreement between pseudo-labels, reaching within 5% to 7% of oracle-tuned performance.
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Interpretable label-free self-guided subspace clustering
A self-guided, label-free hyperparameter tuning method for subspace clustering that splits hyperparameter intervals based on agreement between pseudo-labels, reaching within 5% to 7% of oracle-tuned performance.