Xiaojin Zhang

According to our database, Xiaojin Zhang authored at least 32 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

A Meta-Learning Framework for Tuning Parameters of Protection Mechanisms in Trustworthy Federated Learning.

Xiaojin Zhang, Yan Kang, Lixin Fan, Kai Chen, Qiang Yang

ACM Trans. Intell. Syst. Technol., June, 2024

A Game-theoretic Framework for Privacy-preserving Federated Learning.

Xiaojin Zhang, Lixin Fan, Siwei Wang, Wenjie Li, Kai Chen, Qiang Yang

ACM Trans. Intell. Syst. Technol., June, 2024

Improved algorithm for permutation testing.

Xiaojin Zhang

Theor. Comput. Sci., February, 2024

Corrigendum to "Improved Algorithm for Permutation Testing" [Theoretical Computer Science 986 (2024) 114316].

Xiaojin Zhang

Theor. Comput. Sci., 2024

RSL-SQL: Robust Schema Linking in Text-to-SQL Generation.

Zhenbiao Cao, Yuanlei Zheng, Zhihao Fan, Xiaojin Zhang, Wei Chen, Xiang Bai

CoRR, 2024

MC-CoT: A Modular Collaborative CoT Framework for Zero-shot Medical-VQA with LLM and MLLM Integration.

Lai Wei, Wenkai Wang, Xiaoyu Shen, Yu Xie, Zhihao Fan, Xiaojin Zhang, Zhongyu Wei, Wei Chen

CoRR, 2024

Theoretical Analysis of Privacy Leakage in Trustworthy Federated Learning: A Perspective from Linear Algebra and Optimization Theory.

Xiaojin Zhang, Wei Chen

CoRR, 2024

A Unified Learn-to-Distort-Data Framework for Privacy-Utility Trade-off in Trustworthy Federated Learning.

Xiaojin Zhang, Mingcong Xu, Wei Chen

CoRR, 2024

VulDetectBench: Evaluating the Deep Capability of Vulnerability Detection with Large Language Models.

Yu Liu, Lang Gao, Mingxin Yang, Yu Xie, Ping Chen, Xiaojin Zhang, Wei Chen

CoRR, 2024

No Free Lunch Theorem for Privacy-Preserving LLM Inference.

Xiaojin Zhang, Yulin Fei, Yan Kang, Wei Chen, Lixin Fan, Hai Jin, Qiang Yang

CoRR, 2024

Beyond ESM2: Graph-Enhanced Protein Sequence Modeling with Efficient Clustering.

Shujian Jiao, Bingxuan Li, Lei Wang, Xiaojin Zhang, Wei Chen, Jiajie Peng, Zhongyu Wei

CoRR, 2024

Deciphering the Interplay between Local Differential Privacy, Average Bayesian Privacy, and Maximum Bayesian Privacy.

Xiaojin Zhang, Yulin Fei, Wei Chen

CoRR, 2024

Reinforcement Learning as a Catalyst for Robust and Fair Federated Learning: Deciphering the Dynamics of Client Contributions.

Jialuo He, Wei Chen, Xiaojin Zhang

CoRR, 2024

CauESC: A Causal Aware Model for Emotional Support Conversation.

Wei Chen, Hengxu Lin, Qun Zhang, Xiaojin Zhang, Xiang Bai, Xuanjing Huang, Zhongyu Wei

CoRR, 2024

Secure Dataset Condensation for Privacy-Preserving and Efficient Vertical Federated Learning.

Dashan Gao, Canhui Wu, Xiaojin Zhang, Xin Yao, Qiang Yang

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

Model Trip: Enhancing Privacy and Fairness in Model Fusion Across Multi-Federations for Trustworthy Global Healthcare.

Qian Chen, Yiqiang Chen, Bingjie Yan, Xinlong Jiang, Xiaojin Zhang, Yan Kang, Teng Zhang, Wuliang Huang, Chenlong Gao, Lixin Fan, Qiang Yang

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

2023

Trading Off Privacy, Utility, and Efficiency in Federated Learning.

Xiaojin Zhang, Yan Kang, Kai Chen, Lixin Fan, Qiang Yang

ACM Trans. Intell. Syst. Technol., December, 2023

No Free Lunch Theorem for Security and Utility in Federated Learning.

Xiaojin Zhang, Hanlin Gu, Lixin Fan, Kai Chen, Qiang Yang

ACM Trans. Intell. Syst. Technol., February, 2023

K-ESConv: Knowledge Injection for Emotional Support Dialogue Systems via Prompt Learning.

Wei Chen, Gang Zhao, Xiaojin Zhang, Xiang Bai, Xuanjing Huang, Zhongyu Wei

CoRR, 2023

Privacy in Large Language Models: Attacks, Defenses and Future Directions.

Haoran Li, Yulin Chen, Jinglong Luo, Yan Kang, Xiaojin Zhang, Qi Hu, Chunkit Chan, Yangqiu Song

CoRR, 2023

Theoretically Principled Federated Learning for Balancing Privacy and Utility.

Xiaojin Zhang, Wenjie Li, Kai Chen, Shutao Xia, Qiang Yang

CoRR, 2023

Towards Achieving Near-optimal Utility for Privacy-Preserving Federated Learning via Data Generation and Parameter Distortion.

Xiaojin Zhang, Kai Chen, Qiang Yang

CoRR, 2023

A Game-theoretic Framework for Federated Learning.

Xiaojin Zhang, Lixin Fan, Siwei Wang, Wenjie Li, Kai Chen, Qiang Yang

CoRR, 2023

Probably Approximately Correct Federated Learning.

Xiaojin Zhang, Anbu Huang, Lixin Fan, Kai Chen, Qiang Yang

CoRR, 2023

Toward the Tradeoffs Between Privacy, Fairness and Utility in Federated Learning.

Kangkang Sun, Xiaojin Zhang, Xi Lin, Gaolei Li, Jing Wang, Jianhua Li

Proceedings of the Emerging Information Security and Applications, 2023

2022

A Framework for Evaluating Privacy-Utility Trade-off in Vertical Federated Learning.

Yan Kang, Jiahuan Luo, Yuanqin He, Xiaojin Zhang, Lixin Fan, Qiang Yang

CoRR, 2022

2021

Variance-dependent best arm identification.

Pinyan Lu, Chao Tao, Xiaojin Zhang

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Achieving Near Instance-Optimality and Minimax-Optimality in Stochastic and Adversarial Linear Bandits Simultaneously.

Chung-Wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang, Xiaojin Zhang

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Adaptive Double-Exploration Tradeoff for Outlier Detection.

Xiaojin Zhang, Honglei Zhuang, Shengyu Zhang, Yuan Zhou

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Contextual Combinatorial Conservative Bandits.

Xiaojin Zhang, Shuai Li, Weiwen Liu

CoRR, 2019

Near-Optimal Algorithm for Distribution-Free Junta Testing.

Xiaojin Zhang

CoRR, 2019

Automatic Ensemble Learning for Online Influence Maximization.

Xiaojin Zhang

CoRR, 2019