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Kernelization via Sampling with Applications to Dynamic Graph Streams

Publication at Faculty of Mathematics and Physics |
2016

Abstract

In this paper we present a simple but powerful subgraph sampling primitive that is applicable in a variety of computational models including dynamic graph streams (where the input graph is defined by a sequence of edge/hyperedge insertions and deletions) and distributed systems such as MapReduce.