Thwarting Adversarial Examples: An L_0-Robust Sparse Fourier Transform

NeurIPS 2018 Mitali BafnaJack MurtaghNikhil Vyas

We give a new algorithm for approximating the Discrete Fourier transform of an approximately sparse signal that is robust to worst-case $L_0$ corruptions, namely that some coordinates of the signal can be corrupt arbitrarily. Our techniques generalize to a wide range of linear transformations that are used in data analysis such as the Discrete Cosine and Sine transforms, the Hadamard transform, and their high-dimensional analogs... (read more)

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