output space
Center Smoothing: Certified Robustness for Networks with Structured Outputs
The study of provable adversarial robustness has mostly been limited to classification tasks and models with one-dimensional real-valued outputs. We extend the scope of certifiable robustness to problems with more general and structured outputs like sets, images, language, etc.
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7990ec44fcf3d7a0e5a2add28362213c-Paper.pdf
We propose in this paper a general framework for deriving loss functions for structured prediction. Inourframework,theuserchooses aconvexsetincluding the output space and provides an oracle forprojectingonto that set.
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