Shejwalkar, Virat

Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses for Federated Learning

Shejwalkar, V., & Houmansadr, A. (2021) · Proceedings 2021 Network and Distributed System Security Symposium

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 615

Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated Learning

Shejwalkar, V., Houmansadr, A., Kairouz, P., & Ramage, D. (2022) · 2022 IEEE Symposium on Security and Privacy (SP)

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 292

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Comanici, G., Bieber, E., Schaekermann, M., Pasupat, I., Sachdeva, N., Dhillon, I., Blistein, M., Ram, O., Zhang, D., Rosen, E., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 69