323 citations · 1.3k across the 121 of their papers we have counts for
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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…
Simple Classification using Binary Data
Deanna Needell, Rayan Saab, Tina Woolf
Binary, or one-bit, representations of data arise naturally in many applications, and are appealing in both hardware implementations and algorithm design. In this work, we study th…
Boltzmann Enhancements of Biquasile Counting Invariants
WonHyuk Choi, Deanna Needell, Sam Nelson
In this paper, we build on the biquasiles and dual graph diagrams introduced in arXiv:1610.06969. We introduce \textit{biquasile Boltzmann weights} that enhance the previous knot c…
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…
An Asynchronous Parallel Approach to Sparse Recovery
Deanna Needell, Tina Woolf
Asynchronous parallel computing and sparse recovery are two areas that have received recent interest. Asynchronous algorithms are often studied to solve optimization problems where…