Introduction to Adversarial Machine Learning

Abstract

With all the advances in machine learning and especially in deep learning, you may think that these models are robust and almost perfect in at least the easier tasks such as identifying animals. Unfortunately you’re wrong. While these models have shown great achievements in many tasks, even better than humans, they’re very vulnerable to a family of attacks called Adversarial Attacks, an unsolved problem and an active field of research in machine learning, which we are going to talk about in this presentation

Arian Amani

Data Scientist | Researcher

I am a Computer Science student/researcher at the Sapienza University of Rome, studying, working on, and researching deep learning applications in Life Sciences such as Single-Cell Genomics and Drug Discovery with a focus on Generative Models as a remote research assistant at the Wellcome Sanger Institute.