e-means beats k-means with 10x fewer epochs, now shipped in Meta's FAISS
TimDarcet · x · 2026-11-11
swannbessa introduced e-means, a clustering algorithm that beats k-means with roughly 10x fewer epochs and order-of-magnitude wall-clock speedups. It requires no hyperparameter tuning beyond k, stays robust across scales and datasets, and has been released in Meta's FAISS library. A 10-post technical thread invites skeptics to try it directly.
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