Qinbin Li
Qinbin Li
Postdoc, Computer Science, UC Berkeley
Verified email at - Homepage
Cited by
Cited by
A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection
Q Li, Z Wen, Z Wu, S Hu, N Wang, Y Li, X Liu, B He
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2019
Model-Contrastive Federated Learning
Q Li, B He, D Song
CVPR 2021, 2021
Federated learning on non-iid data silos: An experimental study
Q Li*, Y Diao*, Q Chen, B He
ICDE 2022, 2022
ThunderSVM: A fast SVM library on GPUs and CPUs
Z Wen, J Shi, Q Li, B He, J Chen
The Journal of Machine Learning Research 19 (1), 797-801, 2018
Practical Federated Gradient Boosting Decision Trees
Q Li, Z Wen, B He
AAAI 2020, 2020
Privacy-Preserving Gradient Boosting Decision Trees
Q Li, Z Wu, Z Wen, B He
AAAI 2020, 2020
Practical One-Shot Federated Learning for Cross-Silo Setting
Q Li, B He, D Song
IJCAI 2021, 2021
The oarf benchmark suite: Characterization and implications for federated learning systems
S Hu, Y Li, X Liu, Q Li, Z Wu, B He
ACM Transactions on Intelligent Systems and Technology (TIST), 2021
Exploiting GPUs for efficient gradient boosting decision tree training
Z Wen, J Shi, B He, J Chen, K Ramamohanarao, Q Li
IEEE Transactions on Parallel and Distributed Systems 30 (12), 2706-2717, 2019
ThunderGBM: Fast GBDTs and Random Forests on GPUs
Z Wen, H Liu, J Shi, Q Li, B He, J Chen
The Journal of Machine Learning Research (JMLR), 2020
Practical vertical federated learning with unsupervised representation learning
Z Wu, Q Li, B He
IEEE Transactions on Big Data, 2022
Unifed: A benchmark for federated learning frameworks
X Liu, T Shi, C Xie, Q Li, K Hu, H Kim, X Xu, B Li, D Song
arXiv preprint arXiv:2207.10308, 2022
Adaptive Kernel Value Caching for SVM Training
Q Li, Z Wen, B He
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2019
A Coupled Design of Exploiting Record Similarity for Practical Vertical Federated Learning
Z Wu, Q Li, B He
NeurIPS 2022, 2022
FedTree: A Federated Learning System For Trees
Q Li, Z Wu, Y Cai, Y Han, CM Yung, T Fu, B He
MLSys 2023, 2023
Challenges and Opportunities of Building Fast GBDT Systems
Z Wen, Q Li, B He, B Cui
IJCAI 2021 Survey, 2021
DeltaBoost: Gradient Boosting Decision Trees with Efficient Machine Unlearning
Z Wu, J Zhu, Q Li, B He
SIGMOD 2023, 2023
Towards Addressing Label Skews in One-shot Federated Learning
Y Diao, Q Li, B He
ICLR 2023, 2023
Adversarial Collaborative Learning on Non-IID Features
Q Li, B He, D Song
ICML 2023, 2023
Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks
C Xie, Y Long, PY Chen, Q Li, S Koyejo, B Li
Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications …, 2023
The system can't perform the operation now. Try again later.
Articles 1–20