Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks - researchr publication authors

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Huishuai Zhang, Da Yu, Yiping Lu, Di He. Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks. In Francisco J. R. Ruiz, Jennifer G. Dy, Jan-Willem van de Meent, editors, International Conference on Artificial Intelligence and Statistics, 25-27 April 2023, Palau de Congressos, Valencia, Spain. Volume 206 of Proceedings of Machine Learning Research, pages 2792-2804, PMLR, 2023. [doi]

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