nips nips2009 nips2009-139 nips2009-139-reference knowledge-graph by maker-knowledge-mining

139 nips-2009-Linear-time Algorithms for Pairwise Statistical Problems


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Author: Parikshit Ram, Dongryeol Lee, William March, Alexander G. Gray

Abstract: Several key computational bottlenecks in machine learning involve pairwise distance computations, including all-nearest-neighbors (ďŹ nding the nearest neighbor(s) for each point, e.g. in manifold learning) and kernel summations (e.g. in kernel density estimation or kernel machines). We consider the general, bichromatic case for these problems, in addition to the scientiďŹ c problem of N-body simulation. In this paper we show for the ďŹ rst time O(đ?‘ ) worst case runtimes for practical algorithms for these problems based on the cover tree data structure [1]. 1


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