arXiv cs.LG
· Papers
Mixing Configurations for Downstream Prediction
arXiv:2510.19248v2 Announce Type: replace Abstract: Clustering-based features are widely used in machine learning, but most methods must choose a resolution -- a choice that is global, fixed, and ad hoc. Recent work shows that varying the resolution parameter produces only a finite set of structurally stable partitions