1 citations · 1 across the 3 of their papers we have counts for
3 papers
stat.ML2026
Koopman Operator Identification of Model Parameter Trajectories for Temporal Domain Generalization (KOMET)
Randy C. Hoover, Jacob James, Paul May +1
Parametric models deployed in non-stationary environments degrade as the underlying data distribution evolves over time (a phenomenon known as temporal domain drift). In the curren…
cs.LG2022★ 1 cited
Forecasting Multilinear Data via Transform-Based Tensor Autoregression
Jackson Cates, Randy C. Hoover, Kyle Caudle +3
In the era of big data, there is an increasing demand for new methods for analyzing and forecasting 2-dimensional data. The current research aims to accomplish these goals through…
cs.LG2022
High-Order Multilinear Discriminant Analysis via Order- Tensor Eigendecomposition
Cagri Ozdemir, Randy C. Hoover, Kyle Caudle +1
Higher-order data with high dimensionality is of immense importance in many areas of machine learning, computer vision, and video analytics. Multidimensional arrays (commonly refer…