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In this paper we address the problem of performing statistical inference for large scale data sets. The volume and dimensionality of the data may be so high that it cannot be processed or stored in a single node. We propose a scalable, statistically robust and computationally efficient bootstrap method compatible with distributed processing and storage systems. Bootstrapping is performed on multiple...
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