170 citations · 909 across the 66 of their papers we have counts for
9 papers · 1 filter
Faster Johnson-Lindenstrauss Transforms via Kronecker Products
Ruhui Jin, Tamara G. Kolda, Rachel Ward
The Kronecker product is an important matrix operation with a wide range of applications in supporting fast linear transforms, including signal processing, graph theory, quantum co…
Recovery guarantees for polynomial approximation from dependent data with outliers
Lam Si Tung Ho, Hayden Schaeffer, Giang Tran +1
Learning non-linear systems from noisy, limited, and/or dependent data is an important task across various scientific fields including statistics, engineering, computer science, ma…
Extracting structured dynamical systems using sparse optimization with very few samples
Hayden Schaeffer, Giang Tran, Rachel Ward +1
Learning governing equations allows for deeper understanding of the structure and dynamics of data. We present a random sampling method for learning structured dynamical systems fr…
Randomized Learning of the Second-Moment Matrix of a Smooth Function
Armin Eftekhari, Michael B. Wakin, Ping Li +1
Consider an open set , equipped with a probability measure . An important characteristic of a smooth function $f:\mathbb{D}\rightarrow\mathbb{R}…
Improved bounds for sparse recovery from subsampled random convolutions
Shahar Mendelson, Holger Rauhut, Rachel Ward
We study the recovery of sparse vectors from subsampled random convolutions via -minimization. We consider the setup in which both the subsampling locations as well as the…
MC^2: A Two-Phase Algorithm for Leveraged Matrix Completion
Armin Eftekhari, Michael B. Wakin, Rachel A. Ward
Leverage scores, loosely speaking, reflect the importance of the rows and columns of a matrix. Ideally, given the leverage scores of a rank- matrix ,…
Compressive Sensing with Redundant Dictionaries and Structured Measurements
Felix Krahmer, Deanna Needell, Rachel Ward
Consider the problem of recovering an unknown signal from undersampled measurements, given the knowledge that the signal has a sparse representation in a specified dictionary .…
New and improved Johnson-Lindenstrauss embeddings via the Restricted Isometry Property
Felix Krahmer, Rachel Ward
Consider an m by N matrix Phi with the Restricted Isometry Property of order k and level delta, that is, the norm of any k-sparse vector in R^N is preserved to within a multiplicat…
Lower bounds for the error decay incurred by coarse quantization schemes
Felix Krahmer, Rachel Ward
Several analog-to-digital conversion methods for bandlimited signals used in applications, such as Sigma Delta quantization schemes, employ coarse quantization coupled with oversam…