A new capacity-achieving private information retrieval scheme with (almost) optimal file length for coded servers J Zhu, Q Yan, C Qi, X Tang IEEE Transactions on Information Forensics and Security 15, 1248-1260, 2019 | 35 | 2019 |
Improved constructions for secure multi-party batch matrix multiplication J Zhu, Q Yan, X Tang IEEE Transactions on Communications 69 (11), 7673-7690, 2021 | 20 | 2021 |
Secure batch matrix multiplication from grouping Lagrange encoding J Zhu, X Tang IEEE Communications Letters 25 (4), 1119-1123, 2020 | 19 | 2020 |
Symmetric private polynomial computation from lagrange encoding J Zhu, Q Yan, X Tang, S Li IEEE Transactions on Information Theory 68 (4), 2704-2718, 2022 | 13 | 2022 |
A systematic approach towards efficient private matrix multiplication J Zhu, S Li IEEE Journal on Selected Areas in Information Theory 3 (2), 257-274, 2022 | 12 | 2022 |
Generalized lagrange coded computing: A flexible computation-communication tradeoff J Zhu, S Li 2022 IEEE International Symposium on Information Theory (ISIT), 832-837, 2022 | 10 | 2022 |
Information-theoretically private matrix multiplication from mds-coded storage J Zhu, S Li, J Li IEEE Transactions on Information Forensics and Security 18, 1680-1695, 2023 | 6 | 2023 |
Multi-user blind symmetric private information retrieval from coded servers J Zhu, Q Yan, X Tang IEEE Journal on Selected Areas in Communications 40 (3), 815-831, 2022 | 6 | 2022 |
Capacity-achieving private information retrieval schemes from uncoded storage constrained servers with low sub-packetization J Zhu, Q Yan, X Tang, Y Miao IEEE Transactions on Information Theory 67 (8), 5370-5386, 2021 | 5 | 2021 |
Generalized lagrange coded computing: A flexible computation-communication tradeoff for resilient, secure, and private computation J Zhu, H Tang, S Li, Y Chang arXiv preprint arXiv:2204.11168, 2022 | 1 | 2022 |
Fully privacy-preserving federated representation learning via secure embedding aggregation J Tang, J Zhu, S Li, K Zhang, L Sun Cryptology ePrint Archive, 2022 | 1 | 2022 |
Private Multiple Linear Computation: A Flexible Communication-Computation Tradeoff J Zhu, L Li, X Tang, P Deng arXiv preprint arXiv:2404.09165, 2024 | | 2024 |
Secure Embedding Aggregation for Federated Representation Learning J Tang, J Zhu, S Li, L Sun 2023 IEEE International Symposium on Information Theory (ISIT), 2392-2397, 2023 | | 2023 |
Private Matrix Multiplication From MDS-Coded Storage With Colluding Servers. J Zhu, J Li, S Li CoRR, 2022 | | 2022 |