8 citations · 16 across the 10 of their papers we have counts for
12 papers
Stochastic Natural Thresholding Algorithms
Rachel Grotheer, Shuang Li, Anna Ma +2
Sparse signal recovery is one of the most fundamental problems in various applications, including medical imaging and remote sensing. Many greedy algorithms based on the family of…
Iterative Singular Tube Hard Thresholding Algorithms for Tensor Recovery
Rachel Grotheer, Shuang Li, Anna Ma +2
Due to the explosive growth of large-scale data sets, tensors have been a vital tool to analyze and process high-dimensional data. Different from the matrix case, tensor decomposit…
Automatic Infectious Disease Classification Analysis with Concept Discovery
Elena Sizikova, Joshua Vendrow, Xu Cao +13
Automatic infectious disease classification from images can facilitate needed medical diagnoses. Such an approach can identify diseases, like tuberculosis, which remain under-diagn…
Semi-supervised Nonnegative Matrix Factorization for Document Classification
Jamie Haddock, Lara Kassab, Sixian Li +9
We propose new semi-supervised nonnegative matrix factorization (SSNMF) models for document classification and provide motivation for these models as maximum likelihood estimators.…
Semi-supervised NMF Models for Topic Modeling in Learning Tasks
Jamie Haddock, Lara Kassab, Sixian Li +9
We propose several new models for semi-supervised nonnegative matrix factorization (SSNMF) and provide motivation for SSNMF models as maximum likelihood estimators given specific d…
COVID-19 Literature Topic-Based Search via Hierarchical NMF
Rachel Grotheer, Yihuan Huang, Pengyu Li +7
A dataset of COVID-19-related scientific literature is compiled, combining the articles from several online libraries and selecting those with open access and full text available.…
Stochastic Iterative Hard Thresholding for Low-Tucker-Rank Tensor Recovery
Rachel Grotheer, Shuang Li, Anna Ma +2
Low-rank tensor recovery problems have been widely studied in many applications of signal processing and machine learning. Tucker decomposition is known as one of the most popular…
Iterative Hard Thresholding for Low CP-rank Tensor Models
Rachel Grotheer, Shuang Li, Anna Ma +2
Recovery of low-rank matrices from a small number of linear measurements is now well-known to be possible under various model assumptions on the measurements. Such results demonstr…
Alternatives for Generating a Reduced Basis to Solve the Hyperspectral Diffuse Optical Tomography Model
Rachel Grotheer, Thilo Strauss, Phil Gralla +1
The Reduced Basis Method (RBM) is a model reduction technique used to solve parametric PDEs that relies upon a basis set of solutions to the PDE at specific parameter values. To ge…
Compressed Anomaly Detection with Multiple Mixed Observations
Natalie Durgin, Rachel Grotheer, Chenxi Huang +4
We consider a collection of independent random variables that are identically distributed, except for a small subset which follows a different, anomalous distribution. We study the…
Sparse Randomized Kaczmarz for Support Recovery of Jointly Sparse Corrupted Multiple Measurement Vectors
Natalie Durgin, Rachel Grotheer, Chenxi Huang +4
While single measurement vector (SMV) models have been widely studied in signal processing, there is a surging interest in addressing the multiple measurement vectors (MMV) problem…
Stochastic Greedy Algorithms For Multiple Measurement Vectors
Jing Qin, Shuang Li, Deanna Needell +4
Sparse representation of a single measurement vector (SMV) has been explored in a variety of compressive sensing applications. Recently, SMV models have been extended to solve mult…