We study a subspace constrained version of the randomized Kaczmarz algor...
When solving noisy linear systems Ax = b + c, the theoretical and empiri...
Uncertainty principles present an important theoretical tool in signal
p...
Sketch-and-project is a framework which unifies many known iterative met...
With the growth of large data as well as large-scale learning tasks, the...
Recovery of sparse vectors and low-rank matrices from a small number of
...
We introduce and investigate matrix approximation by decomposition into ...
The California Innocence Project (CIP), a clinical law school program ai...
Fully unsupervised topic models have found fantastic success in document...
We analyze Twitter data relating to the COVID-19 pandemic using dynamic ...
Often in applications ranging from medical imaging and sensor networks t...
A dataset of COVID-19-related scientific literature is compiled, combini...
Projection-based iterative methods for solving large over-determined lin...
We present memory-efficient and scalable algorithms for kernel methods u...