Qinbin Li

According to our database, Qinbin Li authored at least 35 papers between 2018 and 2024.

Collaborative distances:

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

2024

Practical Vertical Federated Learning With Unsupervised Representation Learning.

Zhaomin Wu, Qinbin Li, Bingsheng He

IEEE Trans. Big Data, December, 2024

LLM-PBE: Assessing Data Privacy in Large Language Models.

Qinbin Li, Junyuan Hong, Chulin Xie, Jeffrey Tan, Rachel Xin, Junyi Hou, Xavier Yin, Zhun Wang, Dan Hendrycks, Zhangyang Wang, Bo Li, Bingsheng He, Dawn Song

Proc. VLDB Endow., July, 2024

OEBench: Investigating Open Environment Challenges in Real-World Relational Data Streams.

Yiqun Diao, Yutong Yang, Qinbin Li, Bingsheng He, Mian Lu

Proc. VLDB Endow., February, 2024

ICM-Assistant: Instruction-tuning Multimodal Large Language Models for Rule-based Explainable Image Content Moderation.

Mengyang Wu, Yuzhi Zhao, Jialun Cao, Mingjie Xu, Zhongming Jiang, Xuehui Wang, Qinbin Li, Guangneng Hu, Shengchao Qin, Chi-Wing Fu

CoRR, 2024

Boosting Alignment for Post-Unlearning Text-to-Image Generative Models.

Myeongseob Ko, Henry Li, Zhun Wang, Jonathan Patsenker, Jiachen T. Wang, Qinbin Li, Ming Jin, Dawn Song, Ruoxi Jia

CoRR, 2024

MegaAgent: A Practical Framework for Autonomous Cooperation in Large-Scale LLM Agent Systems.

Qian Wang, Tianyu Wang, Qinbin Li, Jingsheng Liang, Bingsheng He

CoRR, 2024

GuardAgent: Safeguard LLM Agents by a Guard Agent via Knowledge-Enabled Reasoning.

Zhen Xiang, Linzhi Zheng, Yanjie Li, Junyuan Hong, Qinbin Li, Han Xie, Jiawei Zhang, Zidi Xiong, Chulin Xie, Carl Yang, Dawn Song, Bo Li

CoRR, 2024

Federated Learning with New Knowledge: Fundamentals, Advances, and Futures.

Lixu Wang, Yang Zhao, Jiahua Dong, Ating Yin, Qinbin Li, Xiao Wang, Dusit Niyato, Qi Zhu

CoRR, 2024

ModelGo: A Practical Tool for Machine Learning License Analysis.

Moming Duan, Qinbin Li, Bingsheng He

Proceedings of the ACM on Web Conference 2024, 2024

SoK: Privacy-Preserving Data Synthesis.

Yuzheng Hu, Fan Wu, Qinbin Li, Yunhui Long, Gonzalo Munilla Garrido, Chang Ge, Bolin Ding, David A. Forsyth, Bo Li, Dawn Song

Proceedings of the IEEE Symposium on Security and Privacy, 2024

Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM.

Chulin Xie, Pin-Yu Chen, Qinbin Li, Arash Nourian, Ce Zhang, Bo Li

Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2024

Effective and Efficient Federated Tree Learning on Hybrid Data.

Qinbin Li, Chulin Xie, Xiaojun Xu, Xiaoyuan Liu, Ce Zhang, Bo Li, Bingsheng He, Dawn Song

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Exploiting Label Skews in Federated Learning with Model Concatenation.

Yiqun Diao, Qinbin Li, Bingsheng He

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection.

Qinbin Li, Zeyi Wen, Zhaomin Wu, Sixu Hu, Naibo Wang, Yuan Li, Xu Liu, Bingsheng He

IEEE Trans. Knowl. Data Eng., April, 2023

DeltaBoost: Gradient Boosting Decision Trees with Efficient Machine Unlearning.

Zhaomin Wu, Junhui Zhu, Qinbin Li, Bingsheng He

Proc. ACM Manag. Data, 2023

FedTree: A Federated Learning System For Trees.

Qinbin Li, Zhaomin Wu, Yanzheng Cai, Yuxuan Han, Ching Man Yung, Tianyuan Fu, Bingsheng He

Proceedings of the Sixth Conference on Machine Learning and Systems, 2023

Communication-Efficient Generalized Neuron Matching for Federated Learning.

Sixu Hu, Qinbin Li, Bingsheng He

Proceedings of the 52nd International Conference on Parallel Processing, 2023

Adversarial Collaborative Learning on Non-IID Features.

Qinbin Li, Bingsheng He, Dawn Song

Proceedings of the International Conference on Machine Learning, 2023

Towards Addressing Label Skews in One-Shot Federated Learning.

Yiqun Diao, Qinbin Li, Bingsheng He

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks.

Chulin Xie, Yunhui Long, Pin-Yu Chen, Qinbin Li, Sanmi Koyejo, Bo Li

Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 2023

2022

The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems.

Sixu Hu, Yuan Li, Xu Liu, Qinbin Li, Zhaomin Wu, Bingsheng He

ACM Trans. Intell. Syst. Technol., 2022

UniFed: A Benchmark for Federated Learning Frameworks.

Xiaoyuan Liu, Tianneng Shi, Chulin Xie, Qinbin Li, Kangping Hu, Haoyu Kim, Xiaojun Xu, Bo Li, Dawn Song

CoRR, 2022

A Coupled Design of Exploiting Record Similarity for Practical Vertical Federated Learning.

Zhaomin Wu, Qinbin Li, Bingsheng He

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Federated Learning on Non-IID Data Silos: An Experimental Study.

Qinbin Li, Yiqun Diao, Quan Chen, Bingsheng He

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

2021

Challenges and Opportunities of Building Fast GBDT Systems.

Zeyi Wen, Qinbin Li, Bingsheng He, Bin Cui

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Practical One-Shot Federated Learning for Cross-Silo Setting.

Qinbin Li, Bingsheng He, Dawn Song

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Model-Contrastive Federated Learning.

Qinbin Li, Bingsheng He, Dawn Song

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Adaptive Kernel Value Caching for SVM Training.

Qinbin Li, Zeyi Wen, Bingsheng He

IEEE Trans. Neural Networks Learn. Syst., 2020

ThunderGBM: Fast GBDTs and Random Forests on GPUs.

Zeyi Wen, Hanfeng Liu, Jiashuai Shi, Qinbin Li, Bingsheng He, Jian Chen

J. Mach. Learn. Res., 2020

Model-Agnostic Round-Optimal Federated Learning via Knowledge Transfer.

Qinbin Li, Bingsheng He, Dawn Song

CoRR, 2020

Privacy-Preserving Gradient Boosting Decision Trees.

Qinbin Li, Zhaomin Wu, Zeyi Wen, Bingsheng He

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

Practical Federated Gradient Boosting Decision Trees.

Qinbin Li, Zeyi Wen, Bingsheng He

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

2019

Exploiting GPUs for Efficient Gradient Boosting Decision Tree Training.

Zeyi Wen, Jiashuai Shi, Bingsheng He, Jian Chen, Kotagiri Ramamohanarao, Qinbin Li

IEEE Trans. Parallel Distributed Syst., 2019

A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection.

Qinbin Li, Zeyi Wen, Zhaomin Wu, Sixu Hu, Naibo Wang, Xu Liu, Bingsheng He

CoRR, 2019

2018

ThunderSVM: A Fast SVM Library on GPUs and CPUs.

Zeyi Wen, Jiashuai Shi, Qinbin Li, Bingsheng He, Jian Chen

J. Mach. Learn. Res., 2018