11 citations · 24 across the 15 of their papers we have counts for
16 papers
Block Gauss-Seidel methods for t-product tensor regression
Alejandra Castillo, Jamie Haddock, Iryna Hartsock +7
Randomized iterative algorithms, such as the randomized Kaczmarz method and the randomized Gauss-Seidel method, have gained considerable popularity due to their efficacy in solving…
Quantile-Based Randomized Kaczmarz for Corrupted Tensor Linear Systems
Alejandra Castillo, Jamie Haddock, Iryna Hartsock +7
The reconstruction of tensor-valued signals from corrupted measurements, known as tensor regression, has become essential in many multi-modal applications such as hyperspectral ima…
Randomized Kaczmarz methods for t-product tensor linear systems with factorized operators
Alejandra Castillo, Jamie Haddock, Iryna Hartsock +7
Randomized iterative algorithms, such as the randomized Kaczmarz method, have gained considerable popularity due to their efficacy in solving matrix-vector and matrix-matrix regres…
Towards a Fairer Non-negative Matrix Factorization
Lara Kassab, Erin George, Deanna Needell +3
There has been a recent critical need to study fairness and bias in machine learning (ML) algorithms. Since there is clearly no one-size-fits-all solution to fairness, ML methods s…
Stochastic Iterative Methods for Online Rank Aggregation from Pairwise Comparisons
Benjamin Jarman, Lara Kassab, Deanna Needell +1
In this paper, we consider large-scale ranking problems where one is given a set of (possibly non-redundant) pairwise comparisons and the underlying ranking explained by those comp…
Parameters, Properties, and Process: Conditional Neural Generation of Realistic SEM Imagery Towards ML-assisted Advanced Manufacturing
Scott Howland, Lara Kassab, Keerti Kappagantula +2
The research and development cycle of advanced manufacturing processes traditionally requires a large investment of time and resources. Experiments can be expensive and are hence c…
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…
TopTemp: Parsing Precipitate Structure from Temper Topology
Lara Kassab, Scott Howland, Henry Kvinge +2
Technological advances are in part enabled by the development of novel manufacturing processes that give rise to new materials or material property improvements. Development and ev…
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…
Sparseness-constrained Nonnegative Tensor Factorization for Detecting Topics at Different Time Scales
Lara Kassab, Alona Kryshchenko, Hanbaek Lyu +4
Temporal data (such as news articles or Twitter feeds) often consists of a mixture of long-lasting trends and popular but short-lasting topics of interest. A truly successful topic…
An Adaptation for Iterative Structured Matrix Completion
Henry Adams, Lara Kassab, Deanna Needell
The task of predicting missing entries of a matrix, from a subset of known entries, is known as \textit{matrix completion}. In today's data-driven world, data completion is essenti…
On Large-Scale Dynamic Topic Modeling with Nonnegative CP Tensor Decomposition
Miju Ahn, Nicole Eikmeier, Jamie Haddock +7
There is currently an unprecedented demand for large-scale temporal data analysis due to the explosive growth of data. Dynamic topic modeling has been widely used in social and dat…
Multidimensional Scaling on Metric Measure Spaces
Henry Adams, Mark Blumstein, Lara Kassab
Multidimensional scaling (MDS) is a popular technique for mapping a finite metric space into a low-dimensional Euclidean space in a way that best preserves pairwise distances. We o…
Multidimensional Scaling: Infinite Metric Measure Spaces
Lara Kassab
Multidimensional scaling (MDS) is a popular technique for mapping a finite metric space into a low-dimensional Euclidean space in a way that best preserves pairwise distances. We s…
A torus model for optical flow
Henry Adams, Johnathan Bush, Brittany Carr +2
We propose a torus model for high-contrast patches of optical flow. Our model is derived from a database of ground-truth optical flow from the computer-generated video \emph{Sintel…