Local intrinsic dimensionality enables selection of query sets with varying difficulty for nearest neighbor search benchmarking, and common real-world datasets are not diverse as performance on one predicts others well.
In: NIPS 2014 Workshop on Software Engineering for Machine Learning (2014)
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The Role of Local Intrinsic Dimensionality in Benchmarking Nearest Neighbor Search
Local intrinsic dimensionality enables selection of query sets with varying difficulty for nearest neighbor search benchmarking, and common real-world datasets are not diverse as performance on one predicts others well.