I’m excited to open-source e-means: a modern, robust k-means algorithm developed at Meta FAIR. A replacement of Lloyd's algorithm, e-means delivers a ~10× speedup in both epochs and wall-clock time while achieving lower loss.
100,000 datapoints in 200 clusters, two wide Gaussians and three small ones, cut off at a box, on a light uniform background. Lloyd has 1 update against 97 per epoch for e-means.
Across a large range of scales and datasets, e-means reaches a test loss below Lloyd's at 25 epochs, in 1.2 to 3 epochs. Measured end to end, that is a 10–45× wall-clock reduction on GPU against the state-of-the-art Lloyd implementation (Flash-KMeans[2]), and 8–15× on CPU against Faiss[1]. Speed and quality usually trade against each other in k-means, while e-means achieves both better speed and loss.
