8 citations · 20 across the 14 of their papers we have counts for
9 papers · 1 filter
A Systems Theoretic Approach to Online Machine Learning
Anli du Preez, Peter A. Beling, Tyler Cody
The machine learning formulation of online learning is incomplete from a systems theoretic perspective. Typically, machine learning research emphasizes domains and tasks, and a pro…
Metric Learning Improves the Ability of Combinatorial Coverage Metrics to Anticipate Classification Error
Tyler Cody, Laura Freeman
Machine learning models are increasingly used in practice. However, many machine learning methods are sensitive to test or operational data that is dissimilar to training data. Out…
Active Learning with Combinatorial Coverage
Sai Prathyush Katragadda, Tyler Cody, Peter Beling +1
Active learning is a practical field of machine learning that automates the process of selecting which data to label. Current methods are effective in reducing the burden of data l…
Exposing Surveillance Detection Routes via Reinforcement Learning, Attack Graphs, and Cyber Terrain
Lanxiao Huang, Tyler Cody, Christopher Redino +8
Reinforcement learning (RL) operating on attack graphs leveraging cyber terrain principles are used to develop reward and state associated with determination of surveillance detect…
Homomorphisms Between Transfer, Multi-Task, and Meta-Learning Systems
Tyler Cody
Transfer learning, multi-task learning, and meta-learning are well-studied topics concerned with the generalization of knowledge across learning tasks and are closely related to ge…
Systematic Training and Testing for Machine Learning Using Combinatorial Interaction Testing
Tyler Cody, Erin Lanus, Daniel D. Doyle +1
This paper demonstrates the systematic use of combinatorial coverage for selecting and characterizing test and training sets for machine learning models. The presented work adapts…