Kyle A. Caudle

According to our database, Kyle A. Caudle authored at least 17 papers between 2009 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

Forecasting Multilinear Data via Transform-Based Tensor Autoregression.

Jackson Cates, Randy C. Hoover, Kyle A. Caudle, Cagri Ozdemir, Karen S. Braman, David Machette

CoRR, 2022

High-Order Multilinear Discriminant Analysis via Order-n Tensor Eigendecomposition.

Cagri Ozdemir, Randy C. Hoover, Kyle A. Caudle, Karen S. Braman

CoRR, 2022

Kernelization of Tensor Discriminant Analysis with Application to Image Recognition.

Cagri Ozdemir, Randy C. Hoover, Kyle A. Caudle, Karen S. Braman

Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

Anomaly Detection from Multilinear Observations via Time-Series Analysis and 3DTPCA.

Jackson Cates, Randy C. Hoover, Kyle A. Caudle, David J. Marchette, Cagri Ozdemir

Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

2021

A New Approach to Multilinear Dynamical Systems and Control.

Randy C. Hoover, Kyle A. Caudle, Karen S. Braman

CoRR, 2021

Fast Tensor Singular Value Decomposition Using the Low-Resolution Features of Tensors.

Cagri Ozdemir, Randy C. Hoover, Kyle A. Caudle

Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

Transform-Based Tensor Auto Regression for Multilinear Time Series Forecasting.

Jackson Cates, Randy C. Hoover, Kyle A. Caudle, Riley Kopp, Cagri Ozdemir

Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

2DTPCA: A New Framework for Multilinear Principal Component Analysis.

Cagri Ozdemir, Randy C. Hoover, Kyle A. Caudle

Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

2019

Advanced Decision Making and Interpretability through Neural Shrubs.

Kyle A. Caudle, Randy C. Hoover, Aaron Alphonsus, Shashwati Shradha

Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

Building a Better Decision Tree by Delaying the Split Decision.

Kyle A. Caudle, Larry D. Pyeatt, Anthony Morast, Christer Karlsson, Randy C. Hoover

Proceedings of the 3rd International Conference on Compute and Data Analysis, 2019

Flow Field Forecasting with Many Predictors.

Kyle A. Caudle, Patrick Fleming, Larry D. Pyeatt, Randy C. Hoover

Proceedings of the 3rd International Conference on Compute and Data Analysis, 2019

Examining Intermediate Data Reduction Algorithms for use with t-SNE.

Aaron Campbell, Kyle A. Caudle, Randy C. Hoover

Proceedings of the 3rd International Conference on Compute and Data Analysis, 2019

2018

Multilinear Discriminant Analysis Through Tensor-Tensor Eigendecomposition.

Kyle A. Caudle, Randy C. Hoover, Karen S. Braman

Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

2015

Using Density Estimation to Detect Computer Intrusions.

Kyle A. Caudle, Christer Karlsson, Larry D. Pyeatt

Proceedings of the 2015 ACM International Workshop on International Workshop on Security and Privacy Analytics, 2015

2013

Flow field forecasting for univariate time series.

Micheal R. Frey, Kyle A. Caudle

Stat. Anal. Data Min., 2013

2011

Introducing Flow Field Forecasting.

Michael Frey, Kyle A. Caudle

Proceedings of the 10th International Conference on Machine Learning and Applications and Workshops, 2011

2009

Nonparametric density estimation of streaming data using orthogonal series.

Kyle A. Caudle, Edward J. Wegman

Comput. Stat. Data Anal., 2009