Adversarial Forecasting Through Adversarial Risk Analysis Within a DDDAS Framework

Author:

Ekin TahirORCID,Naveiro RoiORCID,Rodriguez Jose Manuel CamachoORCID

Publisher

Springer Nature Switzerland

Reference26 articles.

1. Alfeld, S., Zhu, X., Barford, P.: Data poisoning attacks against autoregressive models. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 30 (2016)

2. Alfeld, S., Zhu, X., Barford, P.: Explicit defense actions against test-set attacks. In: Thirty-First AAAI Conference on Artificial Intelligence (2017)

3. Lecture Notes in Computer Science();C Barreto,2019

4. Blasch, E., Ravela, S., Aved, A.: Handbook of Dynamic Data Driven Applications Systems. Springer, Cham (2018)

5. Brückner, M., Kanzow, C., Scheffer, T.: Static prediction games for adversarial learning problems. J. Mach. Learn. Res. 13(1), 2617–2654 (2012)

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