Streaming algorithms for (k,z)-clustering and Lp subspace embeddings can match offline algorithms in space and time, removing all dependence on stream length n.
Oblivious dimension reduction for k-means: beyond subspaces and the johnson-lindenstrauss lemma
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Fast, Space-Optimal Streaming Algorithms for Clustering and Subspace Embeddings
Streaming algorithms for (k,z)-clustering and Lp subspace embeddings can match offline algorithms in space and time, removing all dependence on stream length n.