Finding Nearest Neighbors in graphs locally
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Many distributed learning techniques have been motivated by the increasing size of datasets and their inability to fit into main memory on a single machine. We propose an algorithm that finds the nearest neighbor in a graph locally without the need of visiting the whole graph. Our algorithm is distributed which further encourage scalability. We prove the convergence of the algorithm
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