A Research Agenda: Dynamic Models to Defend Against Correlated Attacks

arXiv: Learning, 2019.

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Abstract:

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 some of my thoughts about where I think that the field needs to go. Modern machine learning works very well on I.I.D. data: data for which each example is drawn...More

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