3 papers
cs.AI2023
Scope Compliance Uncertainty Estimate
Al-Harith Farhad, Ioannis Sorokos, Mohammed Naveed Akram +2
The zeitgeist of the digital era has been dominated by an expanding integration of Artificial Intelligence~(AI) in a plethora of applications across various domains. With this expa…
cs.LG2023
Explaining black boxes with a SMILE: Statistical Model-agnostic Interpretability with Local Explanations
Koorosh Aslansefat, Mojgan Hashemian, Martin Walker +3
Machine learning is currently undergoing an explosion in capability, popularity, and sophistication. However, one of the major barriers to widespread acceptance of machine learning…
cs.LG2020
SafeML: Safety Monitoring of Machine Learning Classifiers through Statistical Difference Measure
Koorosh Aslansefat, Ioannis Sorokos, Declan Whiting +2
Ensuring safety and explainability of machine learning (ML) is a topic of increasing relevance as data-driven applications venture into safety-critical application domains, traditi…