Kyle A. Caudle

21 papers B 1C 7Journal 8Unranked 5
YearRankTypeTitle / Venue / Authors
2026 J jnl
Koopman Operator Identification of Model Parameter Trajectories for Temporal Domain Generalization (KOMET).
CoRR
Randy C. Hoover, Jacob James, Paul May, Kyle A. Caudle
2025 J jnl
TSGCN: A Framework for Hierarchical Graph Representation Learning.
IEEE Trans. Netw. Sci. Eng.
Jackson Cates, Randy C. Hoover, Kyle A. Caudle, David J. Marchette
2024 C conf
Temporal Tensor Factorization: A Framework for Low-Rank Multilinear Time Series Forecasting.
ICMLA
Jackson Cates, Randy C. Hoover, Kyle A. Caudle, David J. Marchette, Karissa Schipke
2024 J jnl
Tensor discriminant analysis on grassmann manifold with application to video based human action recognition.
Int. J. Mach. Learn. Cybern.
Cagri Ozdemir, Randy C. Hoover, Kyle A. Caudle, Karen S. Braman
2022 C conf
Anomaly Detection from Multilinear Observations via Time-Series Analysis and 3DTPCA.
ICMLA
Jackson Cates, Randy C. Hoover, Kyle A. Caudle, David J. Marchette, Cagri Ozdemir
2022 J jnl
Forecasting Multilinear Data via Transform-Based Tensor Autoregression.
CoRR
Jackson Cates, Randy C. Hoover, Kyle A. Caudle, Cagri Ozdemir, Karen S. Braman, David Machette
2022 J jnl
High-Order Multilinear Discriminant Analysis via Order-n Tensor Eigendecomposition.
CoRR
Cagri Ozdemir, Randy C. Hoover, Kyle A. Caudle, Karen S. Braman
2022 C conf
Kernelization of Tensor Discriminant Analysis with Application to Image Recognition.
ICMLA
Cagri Ozdemir, Randy C. Hoover, Kyle A. Caudle, Karen S. Braman
2021 B conf
2DTPCA: A New Framework for Multilinear Principal Component Analysis.
ICIP
Cagri Ozdemir, Randy C. Hoover, Kyle A. Caudle
2021 J jnl
A New Approach to Multilinear Dynamical Systems and Control.
CoRR
Randy C. Hoover, Kyle A. Caudle, Karen S. Braman
2021 C conf
Fast Tensor Singular Value Decomposition Using the Low-Resolution Features of Tensors.
ICMLA
Cagri Ozdemir, Randy C. Hoover, Kyle A. Caudle
2021 C conf
Transform-Based Tensor Auto Regression for Multilinear Time Series Forecasting.
ICMLA
Jackson Cates, Randy C. Hoover, Kyle A. Caudle, Riley Kopp, Cagri Ozdemir
2019 C conf
Advanced Decision Making and Interpretability through Neural Shrubs.
ICMLA
Kyle A. Caudle, Randy C. Hoover, Aaron Alphonsus, Shashwati Shradha
2019 — conf
Building a Better Decision Tree by Delaying the Split Decision.
ICCDA
Kyle A. Caudle, Larry D. Pyeatt, Anthony Morast, Christer Karlsson, Randy C. Hoover
2019 — conf
Examining Intermediate Data Reduction Algorithms for use with t-SNE.
ICCDA
Aaron Campbell, Kyle A. Caudle, Randy C. Hoover
2019 — conf
Flow Field Forecasting with Many Predictors.
ICCDA
Kyle A. Caudle, Patrick Fleming, Larry D. Pyeatt, Randy C. Hoover
2018 C conf
Multilinear Discriminant Analysis Through Tensor-Tensor Eigendecomposition.
ICMLA
Kyle A. Caudle, Randy C. Hoover, Karen S. Braman
2015 — conf
Using Density Estimation to Detect Computer Intrusions.
IWSPA@CODASPY
Kyle A. Caudle, Christer Karlsson, Larry D. Pyeatt
2013 J jnl
Flow field forecasting for univariate time series.
Stat. Anal. Data Min.
Micheal R. Frey, Kyle A. Caudle
2011 — conf
Introducing Flow Field Forecasting.
ICMLA (1)
Michael Frey, Kyle A. Caudle
2009 J jnl
Nonparametric density estimation of streaming data using orthogonal series.
Comput. Stat. Data Anal.
Kyle A. Caudle, Edward J. Wegman