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Uniform Sampling for Matrix Approximation
Michael B. Cohen, Yin Tat Lee, Cameron Musco +3
Random sampling has become a critical tool in solving massive matrix problems. For linear regression, a small, manageable set of data rows can be randomly selected to approximate a…
Single Pass Spectral Sparsification in Dynamic Streams
Michael Kapralov, Yin Tat Lee, Cameron Musco +2
We present the first single pass algorithm for computing spectral sparsifiers of graphs in the dynamic semi-streaming model. Given a single pass over a stream containing insertions…
Landmark-matching Transformation with Large Deformation via n-dimensional Quasi-conformal Maps
Lee Yin Tat, Lam Ka Chun, Lui Lok Ming
We propose a new method to obtain landmark-matching transformations between n-dimensional Euclidean spaces with large deformations. Given a set of feature correspondences, our algo…