Summary

Proposes novel modification of RBF kernel to mitigate need for hyperparameters in spectral clustering. Uses end-to-end data-driven similarity learning through convex optimization. Achieves SOTA performance on benchmark datasets with linear separation despite data complexity. Future work integrates deep learning models.