6 papers
VDW-GNNs: Vector diffusion wavelets for geometric graph neural networks
David R. Johnson, Alexander Sietsema, Rishabh Anand +3
We introduce vector diffusion wavelets (VDWs), a novel family of wavelets inspired by the vector diffusion maps algorithm that was introduced to analyze data lying in the tangent b…
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…
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…
Stratified Non-Negative Tensor Factorization
Alexander Sietsema, Zerrin Vural, James Chapman +2
Non-negative matrix factorization (NMF) and non-negative tensor factorization (NTF) decompose non-negative high-dimensional data into non-negative low-rank components. NMF and NTF…