arXiv Machine Learning By Abhiyan Dhakal (Kathmandu University), Pranish Kafle (Kathmandu University), Rajani Chulyadyo (Kathmandu University)

Sector-Mean: Deterministic Initialization of K-Means Centroids via Angular Sector Partitioning

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arXiv Machine Learning
Jul 20

Data-Native Global Optimization for Big Data K-means Clustering

arXiv:2607. 15835v1 Announce Type: new Abstract: Big data clustering remains challenging: the Minimum Sum-of-Squares Clustering (MSSC) problem underlying K-means is NP-hard, and existing methods either reach poor local minima or require prohibitive metaheuristic hybrids.

By Ravil Mussabayev, Rustam Mussabayev, Zukhra Yerdaliyeva, Kuldeyev Nursultan
arXiv Machine Learning
Jul 30

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 $\Theta(\log k)$.

By Vaclav Rozhon