3 citations · 4 across the 8 of their papers we have counts for
8 papers
Differentially Private Paired Table-Image Multimodal Synthesis
Kai Chen, Josephine Lamp, Somesh Jha +1
Differentially private (DP) synthesis has been extensively studied for tabular and image data separately, yet many real-world datasets contain images paired with multivariate tabul…
Safety Generalization Under Distribution Shift in Safe Reinforcement Learning: A Diabetes Testbed
Minjae Kwon, Josephine Lamp, Lu Feng
Safe Reinforcement Learning (RL) algorithms are typically evaluated under fixed training conditions. We investigate whether training-time safety guarantees transfer to deployment u…
Quantitative Predictive Monitoring and Control for Safe Human-Machine Interaction
Shuyang Dong, Meiyi Ma, Josephine Lamp +3
There is a growing trend toward AI systems interacting with humans to revolutionize a range of application domains such as healthcare and transportation. However, unsafe human-mach…
DP-RuL: Differentially-Private Rule Learning for Clinical Decision Support Systems
Josephine Lamp, Lu Feng, David Evans
Serious privacy concerns arise with the use of patient data in rule-based clinical decision support systems (CDSS). The goal of a privacy-preserving CDSS is to learn a population r…
CARNA: Characterizing Advanced heart failure Risk and hemodyNAmic phenotypes using learned multi-valued decision diagrams
Josephine Lamp, Yuxin Wu, Steven Lamp +4
Early identification of high risk heart failure (HF) patients is key to timely allocation of life-saving therapies. Hemodynamic assessments can facilitate risk stratification and e…
GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces
Josephine Lamp, Mark Derdzinski, Christopher Hannemann +4
We focus on the problem of generating high-quality, private synthetic glucose traces, a task generalizable to many other time series sources. Existing methods for time series data…
Towards Developing Safety Assurance Cases for Learning-Enabled Medical Cyber-Physical Systems
Maryam Bagheri, Josephine Lamp, Xugui Zhou +2
Machine Learning (ML) technologies have been increasingly adopted in Medical Cyber-Physical Systems (MCPS) to enable smart healthcare. Assuring the safety and effectiveness of lear…
A Logic-Based Learning Approach to Explore Diabetes Patient Behaviors
Josephine Lamp, Simone Silvetti, Marc Breton +2
Type I Diabetes (T1D) is a chronic disease in which the body's ability to synthesize insulin is destroyed. It can be difficult for patients to manage their T1D, as they must contro…