1k citations · 2.4k across the 12 of their papers we have counts for
4 papers · 1 filter
MixMatch: A Holistic Approach to Semi-Supervised Learning
David Berthelot, Nicholas Carlini, Ian Goodfellow +3
Semi-supervised learning has proven to be a powerful paradigm for leveraging unlabeled data to mitigate the reliance on large labeled datasets. In this work, we unify the current d…
A Research Agenda: Dynamic Models to Defend Against Correlated Attacks
Ian Goodfellow
In this article I describe a research agenda for securing machine learning models against adversarial inputs at test time. This article does not present results but instead shares…
Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition
Yao Qin, Nicholas Carlini, Ian Goodfellow +2
Adversarial examples are inputs to machine learning models designed by an adversary to cause an incorrect output. So far, adversarial examples have been studied most extensively in…
On Evaluating Adversarial Robustness
Nicholas Carlini, Anish Athalye, Nicolas Papernot +6
Correctly evaluating defenses against adversarial examples has proven to be extremely difficult. Despite the significant amount of recent work attempting to design defenses that wi…