10 citations · 46 across the 28 of their papers we have counts for
5 papers · 2 filters
Byzantine Resilient Distributed Multi-Task Learning
Jiani Li, Waseem Abbas, Xenofon Koutsoukos
Distributed multi-task learning provides significant advantages in multi-agent networks with heterogeneous data sources where agents aim to learn distinct but correlated models sim…
Trusted Confidence Bounds for Learning Enabled Cyber-Physical Systems
Dimitrios Boursinos, Xenofon Koutsoukos
Cyber-physical systems (CPS) can benefit by the use of learning enabled components (LECs) such as deep neural networks (DNNs) for perception and decision making tasks. However, DNN…
Detecting Adversarial Examples in Learning-Enabled Cyber-Physical Systems using Variational Autoencoder for Regression
Feiyang Cai, Jiani Li, Xenofon Koutsoukos
Learning-enabled components (LECs) are widely used in cyber-physical systems (CPS) since they can handle the uncertainty and variability of the environment and increase the level o…
Real-time Out-of-distribution Detection in Learning-Enabled Cyber-Physical Systems
Feiyang Cai, Xenofon Koutsoukos
Cyber-physical systems (CPS) greatly benefit by using machine learning components that can handle the uncertainty and variability of the real-world. Typical components such as deep…
Assurance Monitoring of Cyber-Physical Systems with Machine Learning Components
Dimitrios Boursinos, Xenofon Koutsoukos
Machine learning components such as deep neural networks are used extensively in Cyber-Physical Systems (CPS). However, they may introduce new types of hazards that can have disast…