60 citations · 234 across the 39 of their papers we have counts for
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Methods of interpreting error estimates for grayscale image reconstructions
Aaron Defazio, Mark Tygert
One representation of possible errors in a grayscale image reconstruction is as another grayscale image estimating potentially worrisome differences between the reconstruction and…
An implementation of a randomized algorithm for principal component analysis
Arthur Szlam, Yuval Kluger, Mark Tygert
Recent years have witnessed intense development of randomized methods for low-rank approximation. These methods target principal component analysis (PCA) and the calculation of tru…
Computing the asymptotic power of a Euclidean-distance test for goodness-of-fit
William Perkins, Gary Simon, Mark Tygert
A natural (yet unconventional) test for goodness-of-fit measures the discrepancy between the model and empirical distributions via their Euclidean distance (or, equivalently, via i…
Computing the confidence levels for a root-mean-square test of goodness-of-fit, II
William Perkins, Mark Tygert, Rachel Ward
This paper extends our earlier article, "Computing the confidence levels for a root-mean-square test of goodness-of-fit;" unlike in the earlier article, the models in the present p…
An algorithm for the principal component analysis of large data sets
Nathan Halko, Per-Gunnar Martinsson, Yoel Shkolnisky +1
Recently popularized randomized methods for principal component analysis (PCA) efficiently and reliably produce nearly optimal accuracy --- even on parallel processors --- unlike t…
Computing the confidence levels for a root-mean-square test of goodness-of-fit
William Perkins, Mark Tygert, Rachel Ward
The classic chi-squared statistic for testing goodness-of-fit has long been a cornerstone of modern statistical practice. The statistic consists of a sum in which each summand invo…