Differentially Private k-Means with Constant Multiplicative Error
NeurIPS, pp. 5436-5446, 2018.
differential privacyfirst timek-means clustering
We design new differentially private algorithms for the Euclidean k-means problem, both in the centralized model and in the local model of differential privacy. In both models, our algorithms achieve significantly improved error guarantees than the previous state-of-the-art. In addition, in the local model, our algorithm significantly red...More
PPT (Upload PPT)