Author:
Ravikanth R.,Jacob T. Prem
Publisher
Springer International Publishing
Reference49 articles.
1. Tramer, F., Kurakin, A., Papernot, N., Goodfellow, I., Boneh, D., & McDaniel, P. (2018). “Ensemble adversarial training: attacks and defenses.” https://arxiv.org/abs/1705.07204.
2. Qiu, X., Zhang, L., Ren, Y., Suganthan, P. N., & Amaratunga, G. (Dec 2014). “Ensemble deep learning for regression and time series forecasting.” In Proceedings of the 2014 IEEE symposium on computational intelligence in ensemble learning (CIEL) (pp. 1–6).
3. Abadi, M., Chu, A., Goodfellow, I. et al. (2016). “Deep learning with differential privacy.” In Proceedings of the 2016 ACM SIGSAC conference on computer and communications security—CCS'16 (pp. 308–318)
4. Phong, L. T., Aono, Y., Hayashi, T., Wang, L., & Moriai, S. (2018). Privacy-preserving deep learning via additively homomorphic encryption. IEEE Transactions on Information Forensics and Security, 13(5), 1333–1345.
5. Papernot, N., McDaniel, P., Wu, X., Jha, S., & Swami, A. (May 2016). “Distillation as a defense to adversarial perturbations against deep neural networks.” In Proceedings of the 2016 IEEE symposium on security and privacy (SP) (pp. 582–597).
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