Scalable Optimization of Neighbor Embedding for Visualization

Abstract

Neighbor embedding (NE) methods have found their use in data visualization but are limited in big data analysis tasks due to their O(n) complexity for n data samples. We demonstrate that the obvious approach of subsampling produces inferior results and propose a generic approximated optimization technique that reduces the NE optimization cost to O(n log n… (More)

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