David Woodruff
Approximation Algorithms for $\ell_0$-Low Rank Approximation
Karl Bringmann, Pavel Kolev, David Woodruff
Neural Information Processing Systems http://nips.cc/
Near Optimal Sketching of Low-Rank Tensor Regression
Xingguo Li, Jarvis Haupt, David Woodruff
We consider the above CP decomposition model of tensors, as well as the Tucker decomposition.
Is Input Sparsity Time Possible for Kernel Low-Rank Approximation?
Cameron Musco, David Woodruff
Low-rank approximation is a common tool used to accelerate kernel methods: the n n kernel matrix K is approximated via a rank-k matrix K which can be stored in much less space and processed more quickly. In this work we study the limits of computationally efficient low-rank kernel approximation.