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- W2803164760 abstract "The $k$-core decomposition is a fundamental primitive in many machine learning and data mining applications. We present the first distributed and the first streaming algorithms to compute and maintain an approximate $k$-core decomposition with provable guarantees. Our algorithms achieve rigorous bounds on space complexity while bounding the number of passes or number of rounds of computation. We do so by presenting a new powerful sketching technique for $k$-core decomposition, and then by showing it can be computed efficiently in both streaming and MapReduce models. Finally, we confirm the effectiveness of our sketching technique empirically on a number of publicly available graphs." @default.
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- W2803164760 date "2018-07-03" @default.
- W2803164760 modified "2023-09-26" @default.
- W2803164760 title "Parallel and Streaming Algorithms for K-Core Decomposition" @default.
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