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2020 – today
- 2024
[j3]Cagri Ozdemir, Randy C. Hoover, Kyle A. Caudle, Karen S. Braman:
Tensor discriminant analysis on grassmann manifold with application to video based human action recognition. Int. J. Mach. Learn. Cybern. 15(8): 3353-3365 (2024)- 2022
- [c12]Cagri Ozdemir, Randy C. Hoover, Kyle A. Caudle, Karen S. Braman:
Kernelization of Tensor Discriminant Analysis with Application to Image Recognition. ICMLA 2022: 183-189 - [c11]Jackson Cates, Randy C. Hoover, Kyle A. Caudle, David J. Marchette, Cagri Ozdemir:
Anomaly Detection from Multilinear Observations via Time-Series Analysis and 3DTPCA. ICMLA 2022: 677-680 - [i3]Cagri Ozdemir, Randy C. Hoover, Kyle A. Caudle, Karen S. Braman:
High-Order Multilinear Discriminant Analysis via Order-n Tensor Eigendecomposition. CoRR abs/2205.09191 (2022) - [i2]Jackson Cates, Randy C. Hoover, Kyle A. Caudle, Cagri Ozdemir, Karen S. Braman, David Machette:
Forecasting Multilinear Data via Transform-Based Tensor Autoregression. CoRR abs/2205.12201 (2022) - 2021
- [c10]Cagri Ozdemir, Randy C. Hoover, Kyle A. Caudle:
2DTPCA: A New Framework for Multilinear Principal Component Analysis. ICIP 2021: 344-348 - [c9]Jackson Cates, Randy C. Hoover, Kyle A. Caudle, Riley Kopp, Cagri Ozdemir:
Transform-Based Tensor Auto Regression for Multilinear Time Series Forecasting. ICMLA 2021: 461-466 - [c8]Cagri Ozdemir, Randy C. Hoover, Kyle A. Caudle:
Fast Tensor Singular Value Decomposition Using the Low-Resolution Features of Tensors. ICMLA 2021: 527-533 - [i1]Randy C. Hoover, Kyle A. Caudle, Karen S. Braman:
A New Approach to Multilinear Dynamical Systems and Control. CoRR abs/2108.13583 (2021)
2010 – 2019
- 2019
- [c7]Aaron Campbell, Kyle A. Caudle, Randy C. Hoover:
Examining Intermediate Data Reduction Algorithms for use with t-SNE. ICCDA 2019: 36-42 - [c6]Kyle A. Caudle, Larry D. Pyeatt, Anthony Morast, Christer Karlsson, Randy C. Hoover:
Building a Better Decision Tree by Delaying the Split Decision. ICCDA 2019: 78-83 - [c5]Kyle A. Caudle, Patrick Fleming, Larry D. Pyeatt, Randy C. Hoover:
Flow Field Forecasting with Many Predictors. ICCDA 2019: 109-115 - [c4]Kyle A. Caudle, Randy C. Hoover, Aaron Alphonsus, Shashwati Shradha:
Advanced Decision Making and Interpretability through Neural Shrubs. ICMLA 2019: 489-494 - 2018
- [c3]Kyle A. Caudle, Randy C. Hoover, Karen S. Braman:
Multilinear Discriminant Analysis Through Tensor-Tensor Eigendecomposition. ICMLA 2018: 578-584 - 2015
- [c2]Kyle A. Caudle, Christer Karlsson, Larry D. Pyeatt:
Using Density Estimation to Detect Computer Intrusions. IWSPA@CODASPY 2015: 43-48 - 2013
- [j2]Micheal R. Frey, Kyle A. Caudle:
Flow field forecasting for univariate time series. Stat. Anal. Data Min. 6(6): 506-518 (2013) - 2011
- [c1]Michael Frey, Kyle A. Caudle:
Introducing Flow Field Forecasting. ICMLA (1) 2011: 395-400
2000 – 2009
- 2009
- [j1]Kyle A. Caudle, Edward J. Wegman:
Nonparametric density estimation of streaming data using orthogonal series. Comput. Stat. Data Anal. 53(12): 3980-3986 (2009)
Coauthor Index
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