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Qinbin Li
Qinbin Li
Verified email at comp.nus.edu.sg - Homepage
Title
Cited by
Cited by
Year
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
271*2019
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
1562018
Model-Contrastive Federated Learning
Q Li, B He, D Song
CVPR 2021, 2021
1082021
Federated learning on non-iid data silos: An experimental study
Q Li*, Y Diao*, Q Chen, B He
ICDE 2022, 2022
1012022
Practical Federated Gradient Boosting Decision Trees
Q Li, Z Wen, B He
AAAI 2020, 2020
832020
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
342019
Privacy-Preserving Gradient Boosting Decision Trees
Q Li, Z Wu, Z Wen, B He
AAAI 2020, 2020
322020
Practical One-Shot Federated Learning for Cross-Silo Setting
Q Li, B He, D Song
IJCAI 2021, 2021
25*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
202021
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
152020
Adaptive Kernel Value Caching for SVM Training
Q Li, Z Wen, B He
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2019
102019
Challenges and Opportunities of Building Fast GBDT Systems
Z Wen, Q Li, B He, B Cui
IJCAI 2021 Survey, 2021
12021
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
2022
Practical Vertical Federated Learning with Unsupervised Representation Learning
Z Wu, Q Li, B He
IEEE Transactions on Big Data, 2022
2022
Adversarial Collaborative Learning on Non-IID Features
Q Li, B He, D Song
2021
Exploiting Record Similarity for Practical Vertical Federated Learning
Z Wu, Q Li, B He
arXiv preprint arXiv:2106.06312, 2021
2021
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