Rates of Convergence for Large-scale Nearest Neighbor Classification

NeurIPS 2019 Xingye QiaoJiexin DuanGuang Cheng

Nearest neighbor is a popular class of classification methods with many desirable properties. For a large data set which cannot be loaded into the memory of a single machine due to computation, communication, privacy, or ownership limitations, we consider the divide and conquer scheme: the entire data set is divided into small subsamples, on which nearest neighbor predictions are made, and then a final decision is reached by aggregating the predictions on subsamples by majority voting... (read more)

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