| Label leakage and protection in two-party split learning O Li, J Sun, X Yang, W Gao, H Zhang, J Xie, V Smith, C Wang arXiv preprint arXiv:2102.08504, 2021 | 116 | 2021 |
| Quadratic suffices for over-parametrization via matrix chernoff bound Z Song, X Yang arXiv preprint arXiv:1906.03593, 2019 | 89 | 2019 |
| FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis B Huang, X Li, Z Song, X Yang International Conference on Machine Learning, 4423-4434, 2021 | 71* | 2021 |
| A near-optimal algorithm for approximating the john ellipsoid MB Cohen, B Cousins, YT Lee, X Yang Conference on Learning Theory, 849-873, 2019 | 45 | 2019 |
| Time-space tradeoffs for learning finite functions from random evaluations, with applications to polynomials P Beame, SO Gharan, X Yang Conference On Learning Theory, 843-856, 2018 | 32 | 2018 |
| Vertical federated learning without revealing intersection membership J Sun, X Yang, Y Yao, A Zhang, W Gao, J Xie, C Wang arXiv preprint arXiv:2106.05508, 2021 | 29 | 2021 |
| Label leakage and protection from forward embedding in vertical federated learning J Sun, X Yang, Y Yao, C Wang arXiv preprint arXiv:2203.01451, 2022 | 25 | 2022 |
| Faster algorithm for structured john ellipsoid computation Z Song, X Yang, Y Yang, T Zhou arXiv preprint arXiv:2211.14407, 2022 | 23 | 2022 |
| Differentially private label protection in split learning X Yang, J Sun, Y Yao, J Xie, C Wang arXiv preprint arXiv:2203.02073, 2022 | 23 | 2022 |
| Sketching meets differential privacy: fast algorithm for dynamic kronecker projection maintenance Z Song, X Yang, Y Yang, L Zhang International Conference on Machine Learning, 32418-32462, 2023 | 19 | 2023 |
| Fast quantum algorithm for attention computation Y Gao, Z Song, X Yang, R Zhang arXiv preprint arXiv:2307.08045, 2023 | 17 | 2023 |
| Differentially private attention computation Y Gao, Z Song, X Yang arXiv preprint arXiv:2305.04701, 2023 | 16 | 2023 |
| Total least squares regression in input sparsity time H Diao, Z Song, D Woodruff, X Yang Advances in Neural Information Processing Systems 32, 2019 | 11 | 2019 |
| Time-space tradeoffs for learning from small test spaces: Learning low degree polynomial functions P Beame, SO Gharan, X Yang arXiv preprint arXiv:1708.02640, 2017 | 10 | 2017 |
| Canaries in the Network D Zhuo, Q Zhang, X Yang, V Liu Proceedings of the 15th ACM Workshop on Hot Topics in Networks, 36-42, 2016 | 10 | 2016 |
| Number balancing is as hard as minkowski’s theorem and shortest vector R Hoberg, H Ramadas, T Rothvoss, X Yang International Conference on Integer Programming and Combinatorial …, 2017 | 9 | 2017 |
| On the Bias of Reed--Muller Codes over Odd Prime Fields P Beame, SO Gharan, X Yang SIAM Journal on Discrete Mathematics 34 (2), 1232-1247, 2020 | 8 | 2020 |
| Netflix and forget: Efficient and exact machine unlearning from bi-linear recommendations M Xu, J Sun, X Yang, K Yao, C Wang arXiv preprint arXiv:2302.06676, 2023 | 7 | 2023 |
| Dpauc: Differentially private auc computation in federated learning J Sun, X Yang, Y Yao, J Xie, D Wu, C Wang Proceedings of the AAAI Conference on Artificial Intelligence 37 (12), 15170 …, 2023 | 4 | 2023 |
| Sketching transformed matrices with applications to natural language processing Y Liang, Z Song, M Wang, L Yang, X Yang International Conference on Artificial Intelligence and Statistics, 467-481, 2020 | 4 | 2020 |
Zhao SongAdobe ResearchVerified email at ias.edu
