no code implementations • 10 May 2019 • Rob Ashmore, Radu Calinescu, Colin Paterson
Our paper provides a comprehensive survey of the state-of-the-art in the assurance of ML, i. e. in the generation of evidence that ML is sufficiently safe for its intended use.
no code implementations • 10 Mar 2018 • Youcheng Sun, Xiaowei Huang, Daniel Kroening, James Sharp, Matthew Hill, Rob Ashmore
In this paper, inspired by the MC/DC coverage criterion, we propose a family of four novel test criteria that are tailored to structural features of DNNs and their semantics.