25 citations · 55 across the 22 of their papers we have counts for
5 papers · 1 filter
Sparse Randomized Kaczmarz for Support Recovery of Jointly Sparse Corrupted Multiple Measurement Vectors
Natalie Durgin, Rachel Grotheer, Chenxi Huang +4
While single measurement vector (SMV) models have been widely studied in signal processing, there is a surging interest in addressing the multiple measurement vectors (MMV) problem…
Stochastic Greedy Algorithms For Multiple Measurement Vectors
Jing Qin, Shuang Li, Deanna Needell +4
Sparse representation of a single measurement vector (SMV) has been explored in a variety of compressive sensing applications. Recently, SMV models have been extended to solve mult…
Unsupervised record matching with noisy and incomplete data
Yves van Gennip, Blake Hunter, Anna Ma +3
We consider the problem of duplicate detection in noisy and incomplete data: given a large data set in which each record has multiple entries (attributes), detect which distinct re…
Stochastic Gradient Descent for Linear Systems with Missing Data
Anna Ma, Deanna Needell
Traditional methods for solving linear systems have quickly become impractical due to an increase in the size of available data. Utilizing massive amounts of data is further compli…
Iterative methods for solving factorized linear systems
Anna Ma, Deanna Needell, Aaditya Ramdas
Stochastic iterative algorithms such as the Kaczmarz and Gauss-Seidel methods have gained recent attention because of their speed, simplicity, and the ability to approximately solv…