Recent Advances in Adversarial Machine Learning

Monday, August 12, 2019 - 9:30 am10:30 am

Nicolas Carlini, Research Scientist, Google Research

Abstract: 

Adversarial machine learning has progressed rapidly over the past few years, with currently over 1,000 papers on this topic and growing at a rate of over a paper a day. In this talk, I survey some of the most interesting recent results, ranging from practical applications of adversarial machine learning to fundamental research investigating why adversarial examples exist in the first place. I conclude with a selection of future research directions that would advance the body of knowledge in this important field.

Nicolas Carlini, Research Scientist, Google Research

Nicholas Carlini is a research scientist at Google Brain. He analyzes the security and privacy of machine learning, for which he has received best paper awards at IEEE S&P and ICML. He graduated with his PhD from the the University of California, Berkeley in 2018.

BibTeX
@conference {238509,
author = {Nicolas Carlini},
title = {Recent Advances in Adversarial Machine Learning},
year = {2019},
address = {Santa Clara, CA},
publisher = {{USENIX} Association},
month = aug,
}