Timestamped state sharing for stream analytics Y Zhao, Z Liu, Y Wu, G Jiang, J Cheng, K Liu, X Yan IEEE Transactions on Parallel and Distributed Systems 32 (11), 2691-2704, 2021 | 4 | 2021 |
Making Privacy-preserving Federated Graph Analytics with Strong Guarantees Practical (for Certain Queries) K Liu, T Gupta arXiv preprint arXiv:2404.01619, 2024 | 1 | 2024 |
Accelerating 2PC-based ML with Limited Trusted Hardware M Nawaz, A Gulati, K Liu, V Agrawal, P Ananth, T Gupta arXiv preprint arXiv:2009.05566, 2020 | 1 | 2020 |
Making Privacy-preserving Federated Graph Analytics Practical (for Certain Queries) K Liu, T Gupta Proceedings of the 29th ACM Symposium on Access Control Models and …, 2024 | | 2024 |
Systems and Methods for Differentially Private Federated Machine Learning for Large Models and a Strong Adversary T Gupta, K Liu, R Wadaskar US Patent App. 18/493,571, 2024 | | 2024 |
Making Privacy-preserving Federated Graph Analytics with Strong Guarantees Practical (for Certain Queries)(preprint) K Liu, T Gupta | | 2024 |
Federated learning with differential privacy and an untrusted aggregator K Liu, T Gupta arXiv preprint arXiv:2312.10789, 2023 | | 2023 |
Towards an Efficient System for Differentially-private, Cross-device Federated Learning K Liu, R Wadaskar, T Gupta Proceedings of the First Workshop on Systems Challenges in Reliable and …, 2021 | | 2021 |