Safety Assurance for Systems with Machine Learning Components
Keywords:Safety, Verification, Neural Networks, Bayesian Learning, Testing, Deep Learning, Machine Learning, Formal Methods, Reinforcement Learning, Validation, AI Safety
AbstractThe use of machine learning components in safety-critical systems creates reliability concerns. My thesis focuses on developing algorithms to address these concerns. Because the assurance of a safety-critical system generally requires multiple types of validation, my research takes three directions: safe deep learning algorithms, formal verification of neural networks, and adaptive testing methods.
How to Cite
Sidrane, C. (2021). Safety Assurance for Systems with Machine Learning Components. Proceedings of the AAAI Conference on Artificial Intelligence, 35(18), 15734-15735. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/17864
The Twenty-Sixth AAAI/SIGAI Doctoral Consortium