Adversarial learning: the impact of statistical sample selection techniques on neural ensembles

Abstract

Adversarial learning is a recently introduced term which refers to the machine learning process in the presence of an adversary whose main goal is to cause dysfunction to the learning machine. The key problem in adversarial learning is to determine when and how an adversary will launch its attacks. It is important to equip the deployed machine learning… (More)
DOI: 10.1007/s12530-010-9013-y

Topics

17 Figures and Tables

Slides referencing similar topics