1.1k citations · 3.5k across the 39 of their papers we have counts for
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Preconditioned Data Sparsification for Big Data with Applications to PCA and K-means
Farhad Pourkamali-Anaraki, Stephen Becker
We analyze a compression scheme for large data sets that randomly keeps a small percentage of the components of each data sample. The benefit is that the output is a sparse matrix…
Robust Partially-Compressed Least-Squares
Stephen Becker, Ban Kawas, Marek Petrik +1
Randomized matrix compression techniques, such as the Johnson-Lindenstrauss transform, have emerged as an effective and practical way for solving large-scale problems efficiently.…
General Optimization Framework for Robust and Regularized 3D Full Waveform Inversion
Stephen Becker, Lior Horesh, Aleksandr Aravkin +1
Scarcity of hydrocarbon resources and high exploration risks motivate the development of high fidelity algorithms and computationally viable approaches to exploratory geophysics. W…
Efficient Dictionary Learning via Very Sparse Random Projections
Farhad Pourkamali-Anaraki, Stephen Becker, Shannon M. Hughes
Performing signal processing tasks on compressive measurements of data has received great attention in recent years. In this paper, we extend previous work on compressive dictionar…