Xiaojin Zhang

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 30

Top Topics

Original Version

Improved Algorithm

Differential Privacy

Top Venues

ACM Trans. Intell. Syst. Technol.

Theor. Comput. Sci.

Publications

Shujian Jiao, Bingxuan Li, Lei Wang, Xiaojin Zhang, Wei Chen, Jiajie Peng, Zhongyu Wei
Beyond ESM2: Graph-Enhanced Protein Sequence Modeling with Efficient Clustering. CoRR (2024)
Xiaojin Zhang
Improved algorithm for permutation testing. Theor. Comput. Sci. 986 (2024)
Qian Chen, Yiqiang Chen, Bingjie Yan, Xinlong Jiang, Xiaojin Zhang, Yan Kang, Teng Zhang, Wuliang Huang, Chenlong Gao, Lixin Fan, Qiang Yang
Model Trip: Enhancing Privacy and Fairness in Model Fusion Across Multi-Federations for Trustworthy Global Healthcare. ICDE (2024)
Xiaojin Zhang, Yan Kang, Lixin Fan, Kai Chen, Qiang Yang
A Meta-Learning Framework for Tuning Parameters of Protection Mechanisms in Trustworthy Federated Learning. ACM Trans. Intell. Syst. Technol. 15 (3) (2024)
Xiaojin Zhang
Corrigendum to "Improved Algorithm for Permutation Testing" [Theoretical Computer Science 986 (2024) 114316]. Theor. Comput. Sci. 999 (2024)
Xiaojin Zhang, Yulin Fei, Yan Kang, Wei Chen, Lixin Fan, Hai Jin, Qiang Yang
No Free Lunch Theorem for Privacy-Preserving LLM Inference. CoRR (2024)
Yu Liu, Lang Gao, Mingxin Yang, Yu Xie, Ping Chen, Xiaojin Zhang, Wei Chen
VulDetectBench: Evaluating the Deep Capability of Vulnerability Detection with Large Language Models. CoRR (2024)
Xiaojin Zhang, Mingcong Xu, Wei Chen
A Unified Learn-to-Distort-Data Framework for Privacy-Utility Trade-off in Trustworthy Federated Learning. CoRR (2024)
Xiaojin Zhang, Yulin Fei, Wei Chen
Deciphering the Interplay between Local Differential Privacy, Average Bayesian Privacy, and Maximum Bayesian Privacy. CoRR (2024)
Xiaojin Zhang, Lixin Fan, Siwei Wang, Wenjie Li, Kai Chen, Qiang Yang
A Game-theoretic Framework for Privacy-preserving Federated Learning. ACM Trans. Intell. Syst. Technol. 15 (3) (2024)
Xiaojin Zhang, Wei Chen
Theoretical Analysis of Privacy Leakage in Trustworthy Federated Learning: A Perspective from Linear Algebra and Optimization Theory. CoRR (2024)
Xiaojin Zhang, Wenjie Li, Kai Chen, Shutao Xia, Qiang Yang
Theoretically Principled Federated Learning for Balancing Privacy and Utility. CoRR (2023)
Xiaojin Zhang, Yan Kang, Kai Chen, Lixin Fan, Qiang Yang
Trading Off Privacy, Utility, and Efficiency in Federated Learning. ACM Trans. Intell. Syst. Technol. 14 (6) (2023)
Xiaojin Zhang, Anbu Huang, Lixin Fan, Kai Chen, Qiang Yang
Probably Approximately Correct Federated Learning. CoRR (2023)
Kangkang Sun, Xiaojin Zhang, Xi Lin, Gaolei Li, Jing Wang, Jianhua Li
Toward the Tradeoffs Between Privacy, Fairness and Utility in Federated Learning. EISA (2023)
Xiaojin Zhang, Yan Kang, Lixin Fan, Kai Chen, Qiang Yang
A Meta-learning Framework for Tuning Parameters of Protection Mechanisms in Trustworthy Federated Learning. CoRR (2023)
Xiaojin Zhang, Hanlin Gu, Lixin Fan, Kai Chen, Qiang Yang
No Free Lunch Theorem for Security and Utility in Federated Learning. ACM Trans. Intell. Syst. Technol. 14 (1) (2023)
Xiaojin Zhang, Yan Kang, Kai Chen, Lixin Fan, Qiang Yang
Trading Off Privacy, Utility and Efficiency in Federated Learning. CoRR (2022)
Xiaojin Zhang, Hanlin Gu, Lixin Fan, Kai Chen, Qiang Yang
No Free Lunch Theorem for Security and Utility in Federated Learning. CoRR (2022)
Yan Kang, Jiahuan Luo, Yuanqin He, Xiaojin Zhang, Lixin Fan, Qiang Yang
A Framework for Evaluating Privacy-Utility Trade-off in Vertical Federated Learning. CoRR (2022)
Pinyan Lu, Chao Tao, Xiaojin Zhang
Variance-Dependent Best Arm Identification. CoRR (2021)
Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang, Xiaojin Zhang
Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously. ICML (2021)
Pinyan Lu, Chao Tao, Xiaojin Zhang
Variance-dependent best arm identification. UAI (2021)
Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang, Xiaojin Zhang
Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously. CoRR (2021)
Xiaojin Zhang, Honglei Zhuang, Shengyu Zhang, Yuan Zhou
Adaptive Double-Exploration Tradeoff for Outlier Detection. AAAI (2020)
Xiaojin Zhang
Improved algorithm for permutation testing. CoRR (2020)
Xiaojin Zhang, Honglei Zhuang, Shengyu Zhang, Yuan Zhou
Adaptive Double-Exploration Tradeoff for Outlier Detection. CoRR (2020)
Xiaojin Zhang
Near-Optimal Algorithm for Distribution-Free Junta Testing. CoRR (2019)
Xiaojin Zhang, Shuai Li, Weiwen Liu
Contextual Combinatorial Conservative Bandits. CoRR (2019)
Xiaojin Zhang
Automatic Ensemble Learning for Online Influence Maximization. CoRR (2019)