Learning With Adversary
Year: 2015
Type: preprint
Abstract: In this paper, we propose a method, learning with adversary, to learn a robust network. Our method takes finding adversarial examples as its mediate step. A new and simple way of finding adversarial examples are presented and experimentally shown to be more `efficient'. Lastly, experimental results shows our learning method greatly improves the robustness of the learned network.
Source: arXiv (Cornell University)
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2135200719