170 citations · 909 across the 66 of their papers we have counts for
17 papers · 1 filter
Scalable symmetric Tucker tensor decomposition
Ruhui Jin, Joe Kileel, Tamara G. Kolda +1
We study the best low-rank Tucker decomposition of symmetric tensors. The motivating application is decomposing higher-order multivariate moments. Moment tensors have special struc…
Learning Dynamical Systems and Bifurcation via Group Sparsity
Hayden Schaeffer, Giang Tran, Rachel Ward
Learning governing equations from a family of data sets which share the same physical laws but differ in bifurcation parameters is challenging. This is due, in part, to the wide ra…
Batched Stochastic Gradient Descent with Weighted Sampling
Deanna Needell, Rachel Ward
We analyze a batched variant of Stochastic Gradient Descent (SGD) with weighted sampling distribution for smooth and non-smooth objective functions. We show that by distributing th…
A near-stationary subspace for ridge approximation
Paul G. Constantine, Armin Eftekhari, Jeffrey Hokanson +1
Response surfaces are common surrogates for expensive computer simulations in engineering analysis. However, the cost of fitting an accurate response surface increases exponentiall…
The sample complexity of weighted sparse approximation
Bubacarr Bah, Rachel Ward
For Gaussian sampling matrices, we provide bounds on the minimal number of measurements required to achieve robust weighted sparse recovery guarantees in terms of how well a gi…
The local convexity of solving systems of quadratic equations
Chris D. White, Sujay Sanghavi, Rachel Ward
This paper considers the recovery of a rank positive semidefinite matrix from scalar measurements of the form (i.e…
Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm
Deanna Needell, Nathan Srebro, Rachel Ward
We obtain an improved finite-sample guarantee on the linear convergence of stochastic gradient descent for smooth and strongly convex objectives, improving from a quadratic depende…
A symbol-based algorithm for decoding bar codes
Mark Iwen, Fadil Santosa, Rachel Ward
We investigate the problem of decoding a bar code from a signal measured with a hand-held laser-based scanner. Rather than formulating the inverse problem as one of binary image re…
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…
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…
Weighted eigenfunction estimates with applications to compressed sensing
Nicolas Burq, Semyon Dyatlov, Rachel Ward +1
Using tools from semiclassical analysis, we give weighted L^\infty estimates for eigenfunctions of strictly convex surfaces of revolution. These estimates give rise to new sampling…
Sparse recovery for spherical harmonic expansions
Holger Rauhut, Rachel Ward
We show that sparse spherical harmonic expansions can be efficiently recovered from a small number of randomly chosen samples on the sphere. To establish the main result, we verify…
Low-rank matrix recovery via iteratively reweighted least squares minimization
Massimo Fornasier, Holger Rauhut, Rachel Ward
We present and analyze an efficient implementation of an iteratively reweighted least squares algorithm for recovering a matrix from a small number of linear measurements. The algo…
Sparse Legendre expansions via minimization
Holger Rauhut, Rachel Ward
We consider the problem of recovering polynomials that are sparse with respect to the basis of Legendre polynomials from a small number of random samples. In particular, we show th…
Iterative thresholding meets free discontinuity problems
Massimo Fornasier, Rachel Ward
Free-discontinuity problems describe situations where the solution of interest is defined by a function and a lower dimensional set consisting of the discontinuities of the functio…
Compressed Sensing with Cross Validation
Rachel Ward
Compressed Sensing decoding algorithms can efficiently recover an N dimensional real-valued vector x to within a factor of its best k-term approximation by taking m = 2klog(N/k) me…