Efficient Coresets for Kernel Clustering with Improved Computational Guarantees

We devise coresets for kernel k-Means and the more general kernel (k,z)-Clustering problems, which significantly improve upon previous results in terms of coreset size and construction time. Our coresets have size poly(kϵ^-1) and can be constructed in near-linear time, enabling efficient algorithms for kernel clustering.