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Adversarial Robustness by Design through Analog Computing and Synthetic Gradients.

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Proving μ>1., , , , и . CoRR, (2020)Robust Neural Networks using Randomized Adversarial Training., , , , , , и . CoRR, (2019)Yet another but more efficient black-box adversarial attack: tiling and evolution strategies., , и . CoRR, (2019)Scalable Lipschitz Residual Networks with Convex Potential Flows., , , и . CoRR, (2021)Variance Reduction for Better Sampling in Continuous Domains., , , и . PPSN (1), том 12269 из Lecture Notes in Computer Science, стр. 154-168. Springer, (2020)Randomization for adversarial robustness: the Good, the Bad and the Ugly., , , и . CoRR, (2023)ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients., , , , и . CoRR, (2021)Adversarial Robustness by Design through Analog Computing and Synthetic Gradients., , , , , и . CoRR, (2021)Adversarial Robustness by Design Through Analog Computing And Synthetic Gradients., , , , , и . ICASSP, стр. 3493-3497. IEEE, (2022)An Asymptotic Test for Conditional Independence using Analytic Kernel Embeddings., , и . ICML, том 162 из Proceedings of Machine Learning Research, стр. 19328-19346. PMLR, (2022)