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- IBM (United States)US73 papers
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4 papers · 2 filters
How Robust are Linear Sketches to Adaptive Inputs?
Moritz Hardt, David P. Woodruff
Linear sketches are powerful algorithmic tools that turn an n-dimensional input into a concise lower-dimensional representation via a linear transformation. Such sketches have seen…
Beyond Worst-Case Analysis in Private Singular Vector Computation
Moritz Hardt, Aaron Roth
We consider differentially private approximate singular vector computation. Known worst-case lower bounds show that the error of any differentially private algorithm must scale pol…
Low Rank Approximation and Regression in Input Sparsity Time
Kenneth L. Clarkson, David P. Woodruff
We design a new distribution over $\poly(r \eps^{-1}) \times n$ matrices so that for any fixed matrix of rank , with probability at least 9/10, $\norm{SAx}_…
The Fast Cauchy Transform and Faster Robust Linear Regression
Kenneth L. Clarkson, Petros Drineas, Malik Magdon-Ismail +3
We provide fast algorithms for overconstrained regression and related problems: for an input matrix and vector , in time we…