28 citations · 70 across the 20 of their papers we have counts for
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On the Impossibility of Dimension Reduction for Doubling Subsets of ,
Yair Bartal, Lee-Ad Gottlieb, Ofer Neiman
A major open problem in the field of metric embedding is the existence of dimension reduction for -point subsets of Euclidean space, such that both distortion and dimension depe…
Efficient Classification for Metric Data
Lee-Ad Gottlieb, Aryeh Kontorovich, Robert Krauthgamer
Recent advances in large-margin classification of data residing in general metric spaces (rather than Hilbert spaces) enable classification under various natural metrics, such as s…
Adaptive Metric Dimensionality Reduction
Lee-Ad Gottlieb, Aryeh Kontorovich, Robert Krauthgamer
We study adaptive data-dependent dimensionality reduction in the context of supervised learning in general metric spaces. Our main statistical contribution is a generalization boun…