Scalable Clustering: Large Scale Unsupervised Learning of Gaussian Mixture Models with Outliers

no code implementations • 28 Feb 2023 • Yijia Zhou, Kyle A. Gallivan, Adrian Barbu

Experiments on real-world large-scale datasets demonstrate the effectiveness of the algorithm when clustering a large number of clusters, and a $k$-means algorithm initialized by the algorithm outperforms many of the classic clustering methods in both speed and accuracy, while scaling well to large datasets such as ImageNet.

Clustering