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Christian Cianfarani

2 accepted papers

2025

Adapting to Evolving Adversaries with Regularized Continual Robust Training

ICML 2025poster

Robust training methods typically defend against specific attack types, such as $\ell_p$ attacks with fixed budgets, and rarely account for the fact that defenders may encounter new attacks over time. A natural solution is to adapt the defended model to new adversaries as they arise via fine-tuning…

2022

Understanding Robust Learning through the Lens of Representation Similarities

NeurIPS 2022accept

Representation learning, \textit{i.e.} the generation of representations useful for downstream applications, is a task of fundamental importance that underlies much of the success of deep neural networks (DNNs). Recently, \emph{robustness to adversarial examples} has emerged as a desirable property…