Evans, David

Advances and Open Problems in Federated Learning

Kairouz, P., McMahan, H. B., Avent, B., Bellet, A., Bennis, M., Bhagoji, A. N., Bonawitz, K., Charles, Z., Cormode, G., Cummings, R., et al. (2019) · arXiv

Privacy-Preserving Technologies in DataStochastic Gradient Optimization Techniques

Cited by 7,857

Evaluating Differentially Private Machine Learning in Practice

Jayaraman, B., & Evans, D. (2019) · arXiv

Privacy-Preserving Technologies in DataPrivacy, Security, and Data Protection

Cited by 265

Privacy-preserving distributed linear regression on high-dimensional data

Gascón, A., Schoppmann, P., Balle, B., Raykova, M., Doerner, J., Zahur, S., & Evans, D. (2017) · Proceedings on Privacy Enhancing Technologies

Cryptography and Data SecurityPrivacy-Preserving Technologies in Data

Cited by 193

Security issues and requirements for Internet-scale publish-subscribe systems

Wang, C., Carzaniga, A., Evans, D., & Wolf, A. L. (2003) · Proceedings of the 35th Annual Hawaii International Conference on System Sciences

Access Control and TrustPeer-to-Peer Network Technologies

Cited by 176

Do Membership Inference Attacks Work on Large Language Models?

Duan, M., Suri, A., Mireshghallah, N., Min, S., Shi, W., Zettlemoyer, L., Tsvetkov, Y., Choi, Y., Evans, D., & Hajishirzi, H. (2024) · arXiv

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 17