27 citations · 66 across the 3 of their papers we have counts for
5 papers
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…
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…
Weighted -Minimization for Sparse Recovery under Arbitrary Prior Information
Deanna Needell, Rayan Saab, Tina Woolf
Weighted -minimization has been studied as a technique for the reconstruction of a sparse signal from compressively sampled measurements when prior information about the si…
Constrained adaptive sensing
Mark A. Davenport, Andrew K. Massimino, Deanna Needell +1
Suppose that we wish to estimate a vector from a small number of noisy linear measurements of the form , where…
Linear Convergence of Stochastic Iterative Greedy Algorithms with Sparse Constraints
Nam Nguyen, Deanna Needell, Tina Woolf
Motivated by recent work on stochastic gradient descent methods, we develop two stochastic variants of greedy algorithms for possibly non-convex optimization problems with sparsity…