A Theoretically Grounded Extension of Universal Attacks from the Attacker’s Viewpoint

Author:

Patracone Jordan,Viallard Paul,Morvant Emilie,Gasso Gilles,Habrard Amaury,Canu Stéphane

Publisher

Springer Nature Switzerland

Reference57 articles.

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3. Awasthi, P., Frank, N., Mohri, M.: Adversarial learning guarantees for linear hypotheses and neural networks. In: ICML (2020)

4. Baluja, S., Fischer, I.: Learning to attack: adversarial transformation networks. In: AAAI, vol. 32, no. 1 (2018)

5. Bartlett, P.L., Boucheron, S., Lugosi, G.: Model selection and error estimation. Mach. Learn. 48(1–3), 85–113 (2002)

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