| pGlyco 2.0 enables precision N-glycoproteomics with comprehensive quality control and one-step mass spectrometry for intact glycopeptide identification MQ Liu, WF Zeng, P Fang, WQ Cao, C Liu, GQ Yan, Y Zhang, C Peng, ... Nature communications 8 (1), 438, 2017 | 273 | 2017 |
| Achieving near instance-optimality and minimax-optimality in stochastic and adversarial linear bandits simultaneously CW Lee, H Luo, CY Wei, M Zhang, X Zhang International Conference on Machine Learning, 6142-6151, 2021 | 44 | 2021 |
| No free lunch theorem for security and utility in federated learning X Zhang, H Gu, L Fan, K Chen, Q Yang ACM Transactions on Intelligent Systems and Technology 14 (1), 1-35, 2022 | 43 | 2022 |
| Trading Off Privacy, Utility, and Efficiency in Federated Learning X Zhang, Y Kang, K Chen, L Fan, Q Yang ACM Transactions on Intelligent Systems and Technology 14 (6), 1-32, 2023 | 22 | 2023 |
| Privacy in large language models: Attacks, defenses and future directions H Li, Y Chen, J Luo, Y Kang, X Zhang, Q Hu, C Chan, Y Song arXiv preprint arXiv:2310.10383, 2023 | 15 | 2023 |
| A framework for evaluating privacy-utility trade-off in vertical federated learning Y Kang, J Luo, Y He, X Zhang, L Fan, Q Yang arXiv preprint arXiv:2209.03885, 2022 | 12 | 2022 |
| Variance-dependent best arm identification P Lu, C Tao, X Zhang Uncertainty in Artificial Intelligence, 1120-1129, 2021 | 11 | 2021 |
| Probably Approximately Correct Federated Learning X Zhang, A Huang, L Fan, K Chen, Q Yang arXiv preprint arXiv:2304.04641, 2023 | 6* | 2023 |
| Contextual combinatorial conservative bandits X Zhang, S Li, W Liu, S Zhang arXiv preprint arXiv:1911.11337, 2019 | 5 | 2019 |
| Near-optimal algorithm for distribution-free junta testing X Zhang arXiv preprint arXiv:1911.10833, 2019 | 3 | 2019 |
| Trends in mass spectrometry-based large-scale N-glycopeptides analysis Z Wen-Feng, Z Yang, L Ming-Qi, W Jian-Qiang, Z Xiao-Jin, Y Hao, L Chao, ... CHINESE ACAD SCIENCES, INST BIOPHYSICS 43 (6), 2016 | 3 | 2016 |
| Grounding foundation models through federated transfer learning: A general framework Y Kang, T Fan, H Gu, X Zhang, L Fan, Q Yang arXiv preprint arXiv:2311.17431, 2023 | 2 | 2023 |
| Theoretically Principled Federated Learning for Balancing Privacy and Utility X Zhang, W Li, K Chen, S Xia, Q Yang arXiv preprint arXiv:2305.15148, 2023 | 2 | 2023 |
| Towards Achieving Near-optimal Utility for Privacy-Preserving Federated Learning via Data Generation and Parameter Distortion X Zhang, K Chen, Q Yang arXiv preprint arXiv:2305.04288, 2023 | 2 | 2023 |
| A Game-theoretic Framework for Privacy-preserving Federated Learning X Zhang, L Fan, S Wang, W Li, K Chen, Q Yang arXiv preprint arXiv:2304.05836, 2023 | 2 | 2023 |
| K-esconv: Knowledge injection for emotional support dialogue systems via prompt learning W Chen, G Zhao, X Zhang, X Bai, X Huang, Z Wei arXiv preprint arXiv:2312.10371, 2023 | 1 | 2023 |
| A Meta-learning Framework for Tuning Parameters of Protection Mechanisms in Trustworthy Federated Learning X Zhang, Y Kang, L Fan, K Chen, Q Yang ACM Transactions on Intelligent Systems and Technology, 2023 | 1 | 2023 |
| Automatic ensemble learning for online influence maximization X Zhang arXiv preprint arXiv:1911.10728, 2019 | 1 | 2019 |
| Deciphering the Interplay between Local Differential Privacy, Average Bayesian Privacy, and Maximum Bayesian Privacy X Zhang, Y Fei, W Chen arXiv preprint arXiv:2403.16591, 2024 | | 2024 |
| Improved algorithm for permutation testing X Zhang Theoretical Computer Science 986, 114316, 2024 | | 2024 |
Qiang Yang (杨强）Chief AI Officer@WeBank, Prof. Emeritus @HKUST, IJCAI President 2017-19, AAAI-21 General ChairVerified email at cse.ust.hk
