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Optimality of the Johnson-Lindenstrauss Dimensionality Reduction for Practical Measures
They provided upper bounds on its quality for a wide range of practical measures and showed that indeed these are best possible in many cases.
Dimensionality reduction: theoretical perspective on practical measures
In this paper we provide the first analysis of these, as well as the new distortion measure developed by [VL18] designed to possess Machine Learning desired properties.
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