323 citations · 1.3k across the 121 of their papers we have counts for
7 papers · 1 filter
Spectral Clustering: An empirical study of Approximation Algorithms and its Application to the Attrition Problem
B. Cung, T. Jin, J. Ramirez +3
Clustering is the problem of separating a set of objects into groups (called clusters) so that objects within the same cluster are more similar to each other than to those in diffe…
Near-optimal compressed sensing guarantees for total variation minimization
Deanna Needell, Rachel Ward
Consider the problem of reconstructing a multidimensional signal from an underdetermined set of measurements, as in the setting of compressed sensing. Without any additional assump…
Paved with Good Intentions: Analysis of a Randomized Block Kaczmarz Method
Deanna Needell, Joel A. Tropp
The block Kaczmarz method is an iterative scheme for solving overdetermined least-squares problems. At each step, the algorithm projects the current iterate onto the solution space…
Signal Space CoSaMP for Sparse Recovery with Redundant Dictionaries
Mark A. Davenport, Deanna Needell, Michael B. Wakin
Compressive sensing (CS) has recently emerged as a powerful framework for acquiring sparse signals. The bulk of the CS literature has focused on the case where the acquired signal…
Two-subspace Projection Method for Coherent Overdetermined Systems (Technical Report)
Deanna Needell, Rachel Ward
In this technical report we present a Projection onto Convex Sets (POCS) type algorithm for solving systems of linear equations. POCS methods have found many applications ranging f…
Two-subspace Projection Method for Coherent Overdetermined Systems
Deanna Needell, Rachel Ward
We present a Projection onto Convex Sets (POCS) type algorithm for solving systems of linear equations. POCS methods have found many applications ranging from computer tomography t…