arXiv stat.ML
· Papers
Randomizing the Number of Centers in k-means++
arXiv:2607.26202v1 Announce Type: cross Abstract: The $k$-means++ algorithm is a standard and widely used seeding method for $k$-means clustering, but for a fixed number $k$ of centers its worst-case expected approximation ratio is $Theta(log k)$. We consider the same algorithm when an adversary first fixes the datas