1 citations · 1 across the 5 of their papers we have counts for
5 papers
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…
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…
Core and Periphery as Closed-System Precepts for Engineering General Intelligence
Tyler Cody, Niloofar Shadab, Alejandro Salado +1
Engineering methods are centered around traditional notions of decomposition and recomposition that rely on partitioning the inputs and outputs of components to allow for component…
Discovering Exfiltration Paths Using Reinforcement Learning with Attack Graphs
Tyler Cody, Abdul Rahman, Christopher Redino +7
Reinforcement learning (RL), in conjunction with attack graphs and cyber terrain, are used to develop reward and state associated with determination of optimal paths for exfiltrati…