no code implementations • 9 Nov 2018 • Thomas A. Hogan, Bhavya Kailkhura
We study the problem of finding a universal (image-agnostic) perturbation to fool machine learning (ML) classifiers (e. g., neural nets, decision tress) in the hard-label black-box setting.
