1.3k citations · 4.9k across the 150 of their papers we have counts for
9 papers · 1 filter
Time-varying Learning and Content Analytics via Sparse Factor Analysis
Andrew S. Lan, Christoph Studer, Richard G. Baraniuk
We propose SPARFA-Trace, a new machine learning-based framework for time-varying learning and content analytics for education applications. We develop a novel message passing-based…
Swapping Variables for High-Dimensional Sparse Regression with Correlated Measurements
Divyanshu Vats, Richard G. Baraniuk
We consider the high-dimensional sparse linear regression problem of accurately estimating a sparse vector using a small number of linear measurements that are contaminated by nois…
The STONE Transform: Multi-Resolution Image Enhancement and Real-Time Compressive Video
Tom Goldstein, Lina Xu, Kevin F. Kelly +1
Compressed sensing enables the reconstruction of high-resolution signals from under-sampled data. While compressive methods simplify data acquisition, they require the solution of…
Parameterless Optimal Approximate Message Passing
Ali Mousavi, Arian Maleki, Richard G. Baraniuk
Iterative thresholding algorithms are well-suited for high-dimensional problems in sparse recovery and compressive sensing. The performance of this class of algorithms depends heav…
Asymptotic Analysis of LASSOs Solution Path with Implications for Approximate Message Passing
Ali Mousavi, Arian Maleki, Richard G. Baraniuk
This paper concerns the performance of the LASSO (also knows as basis pursuit denoising) for recovering sparse signals from undersampled, randomized, noisy measurements. We conside…
Joint Topic Modeling and Factor Analysis of Textual Information and Graded Response Data
Andrew S. Lan, Christoph Studer, Andrew E. Waters +1
Modern machine learning methods are critical to the development of large-scale personalized learning systems that cater directly to the needs of individual learners. The recently d…