Publications

Preprint

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
arxiv. [PDF][code]

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
The Twelfth International Conference on Learning Representations. ICLR 2024

OEBench: Investigating Open Environment Challenges in Real-World Relational Data Streams
Yiqun Diao, Yutong Yang, Qinbin Li^, Bingsheng He, Mian Lu (^ denotes corresponding author)
50th International Conference on Very Large Databases. VLDB 2024

Exploiting Label Skews in Federated Learning with Model Concatenation
Yiqun Diao, Qinbin Li, Bingsheng He
The 38th Annual AAAI Conference on Artificial Intelligence. AAAI 2024

SoK: Privacy-Preserving Data Synthesis
Yuzheng Hu, Fan Wu, Qinbin Li, Yunhui Long, Gonzalo Munilla Garrido, Chang Ge, Bolin Ding, David Forsyth, Bo Li, Dawn Song
45th IEEE Symposium on Security and Privacy. S&P 2024

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
ACM Conference on Computer and Communications Security. CCS 2023

Communication-Efficient Generalized Neuron Matching for Federated Learning
Sixu Hu, Qinbin Li, Bingsheng He
52nd International Conference on Parallel Processing. ICPP 2023

Adversarial Collaborative Learning on Non-IID Features
Qinbin Li, Bingsheng He, Dawn Song
Fortieth International Conference on Machine Learning. ICML 2023

DeltaBoost: Gradient Boosting Decision Trees with Efficient Machine Unlearning
Zhaomin Wu, Junhui Zhu, Qinbin Li, Bingsheng He
The 2023 International Conference on Management of Data. SIGMOD 2023

FedTree: A Federated Learning System For Trees
Qinbin Li, Zhaomin Wu, Yanzheng Cai, Yuxuan Han, Ching Man Yung, Tianyuan Fu, Bingsheng He
Sixth Conference on Machine Learning and Systems. MLSys 2023 [code]

Towards Addressing Label Skews in One-Shot Federated Learning
Yiqun Diao, Qinbin Li, Bingsheng He
The Eleventh International Conference on Learning Representations. ICLR 2023 [PDF][code]

2022

A Coupled Design of Exploiting Record Similarity for Practical Vertical Federated Learning
Zhaomin Wu, Qinbin Li, Bingsheng He
Thirty-sixth Conference on Neural Information Processing Systems. NeurIPS 2022 [PDF][code]

Federated Learning on Non-IID Data Silos: An Experimental Study
Qinbin Li, Yiqun Diao, Quan Chen, Bingsheng He (* denotes equal contributions)
IEEE International Conference on Data Engineering. ICDE 2022 [PDF][code]

Practical Vertical Federated Learning with Unsupervised Representation Learning
Zhaomin Wu, Qinbin Li, Bingsheng He
IEEE Transactions on Big Data. TBD 2022 [PDF][code]

2021

The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems
Sixu Hu, Yuan Li, Xu Liu, Qinbin Li, Zhaomin Wu, Bingsheng He
ACM Transactions on Intelligent Systems and Technology. TIST 2021 [PDF][code]

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 Transactions on Knowledge and Data Engineering. TKDE 2021 [PDF]

Practical One-Shot Federated Learning for Cross-Silo Setting
Qinbin Li, Bingsheng He, Dawn Song
International Joint Conference on Artificial Intelligence IJCAI 2021 [PDF][code]

Challenges and Opportunies of Building Fast GBDT Systems
Zeyi Wen, Qinbin Li, Bingsheng He, Bin Cui
International Joint Conference on Artificial Intelligence IJCAI 2021 survey track [PDF].

Model-Contrastive Federated Learning
Qinbin Li, Bingsheng He, Dawn Song
The Conference on Computer Vision and Pattern Recognition CVPR 2021. [PDF][code]

2020

ThunderGBM: Fast GBDTs and Random Forests on GPUs
Zeyi Wen, Hanfeng Liu, Jiashuai Shi, Qinbin Li, Bingsheng He, Jian Chen
Journal of Machine Learning Research. JMLR 2020. [PDF][code]

Practical Federated Gradient Boosting Decision Trees
Qinbin Li, Zeyi Wen, Bingsheng He
Thirty-Fourth AAAI Conference on Artificial Intelligence. AAAI 2020. PREMIA Best Student Paper Gold Award. [PDF]

Privacy-Preserving Gradient Boosting Decision Trees
Qinbin Li, Zhaomin Wu, Zeyi Wen, Bingsheng He
Thirty-Fourth AAAI Conference on Artificial Intelligence. AAAI 2020. [PDF][code]

2019

Adaptive Kernel Value Caching for SVM Training
Qinbin Li, Zeyi Wen, Bingsheng He
IEEE Transactions on Neural Networks and Learning Systems. TNNLS 2019. [PDF][code]

Exploiting GPUs for Efficient Gradient Boosting Decision Tree Training
Zeyi Wen, Jiashuai Shi, Bingsheng He, Jian Chen, Kotagiri Ramamohanarao, Qinbin Li
IEEE Transactions on Parallel and Distributed Systems. TPDS 2019 Best Paper Award. [PDF][code]

2018

ThunderSVM: A Fast SVM Library on GPUs and CPUs
Zeyi Wen, Jiashuai Shi, Qinbin Li, Bingsheng He, Jian Chen
Journal of Machine Learning Research. JMLR 2018. [PDF][code]