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2020 – today
- 2023
[j6]Qinbin Li
, Zeyi Wen, Zhaomin Wu, Sixu Hu, Naibo Wang, Yuan Li, Xu Liu, Bingsheng He:
A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection. IEEE Trans. Knowl. Data Eng. 35(4): 3347-3366 (2023)- 2022
- [j5]Sixu Hu, Yuan Li, Xu Liu, Qinbin Li, Zhaomin Wu, Bingsheng He:
The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems. ACM Trans. Intell. Syst. Technol. 13(4): 63:1-63:32 (2022) - [c7]Qinbin Li, Yiqun Diao, Quan Chen, Bingsheng He:
Federated Learning on Non-IID Data Silos: An Experimental Study. ICDE 2022: 965-978 - [c6]Zhaomin Wu, Qinbin Li, Bingsheng He:
A Coupled Design of Exploiting Record Similarity for Practical Vertical Federated Learning. NeurIPS 2022 - [i11]Xiaoyuan Liu, Tianneng Shi, Chulin Xie, Qinbin Li, Kangping Hu, Haoyu Kim, Xiaojun Xu, Bo Li, Dawn Song:
UniFed: A Benchmark for Federated Learning Frameworks. CoRR abs/2207.10308 (2022) - [i10]Zhaomin Wu, Qinbin Li, Bingsheng He:
Practical Vertical Federated Learning with Unsupervised Representation Learning. CoRR abs/2208.10278 (2022) - 2021
- [c5]Qinbin Li, Bingsheng He, Dawn Song:
Model-Contrastive Federated Learning. CVPR 2021: 10713-10722 - [c4]Qinbin Li, Bingsheng He, Dawn Song:
Practical One-Shot Federated Learning for Cross-Silo Setting. IJCAI 2021: 1484-1490 - [c3]Zeyi Wen, Qinbin Li, Bingsheng He, Bin Cui:
Challenges and Opportunities of Building Fast GBDT Systems. IJCAI 2021: 4661-4668 - [i9]Qinbin Li, Yiqun Diao, Quan Chen, Bingsheng He:
Federated Learning on Non-IID Data Silos: An Experimental Study. CoRR abs/2102.02079 (2021) - [i8]Qinbin Li, Bingsheng He, Dawn Song:
Model-Contrastive Federated Learning. CoRR abs/2103.16257 (2021) - [i7]Zhaomin Wu, Qinbin Li, Bingsheng He:
A Coupled Design of Exploiting Record Similarity for Practical Vertical Federated Learning. CoRR abs/2106.06312 (2021) - 2020
- [j4]Zeyi Wen, Hanfeng Liu, Jiashuai Shi, Qinbin Li, Bingsheng He, Jian Chen:
ThunderGBM: Fast GBDTs and Random Forests on GPUs. J. Mach. Learn. Res. 21: 108:1-108:5 (2020) - [j3]Qinbin Li, Zeyi Wen, Bingsheng He:
Adaptive Kernel Value Caching for SVM Training. IEEE Trans. Neural Networks Learn. Syst. 31(7): 2376-2386 (2020) - [c2]Qinbin Li, Zhaomin Wu, Zeyi Wen, Bingsheng He:
Privacy-Preserving Gradient Boosting Decision Trees. AAAI 2020: 784-791 - [c1]Qinbin Li, Zeyi Wen, Bingsheng He:
Practical Federated Gradient Boosting Decision Trees. AAAI 2020: 4642-4649 - [i6]Sixu Hu, Yuan Li, Xu Liu, Qinbin Li, Zhaomin Wu, Bingsheng He:
The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems. CoRR abs/2006.07856 (2020) - [i5]Qinbin Li, Bingsheng He, Dawn Song:
Model-Agnostic Round-Optimal Federated Learning via Knowledge Transfer. CoRR abs/2010.01017 (2020)
2010 – 2019
- 2019
- [j2]Zeyi Wen, Jiashuai Shi, Bingsheng He, Jian Chen, Kotagiri Ramamohanarao, Qinbin Li:
Exploiting GPUs for Efficient Gradient Boosting Decision Tree Training. IEEE Trans. Parallel Distributed Syst. 30(12): 2706-2717 (2019) - [i4]Qinbin Li, Zeyi Wen, Zhaomin Wu, Sixu Hu, Naibo Wang, Xu Liu, Bingsheng He:
A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection. CoRR abs/1907.09693 (2019) - [i3]Qinbin Li, Zeyi Wen, Bingsheng He:
Adaptive Kernel Value Caching for SVM Training. CoRR abs/1911.03011 (2019) - [i2]Qinbin Li, Zeyi Wen, Bingsheng He:
Practical Federated Gradient Boosting Decision Trees. CoRR abs/1911.04206 (2019) - [i1]Qinbin Li, Zhaomin Wu, Zeyi Wen, Bingsheng He:
Privacy-Preserving Gradient Boosting Decision Trees. CoRR abs/1911.04209 (2019) - 2018
- [j1]Zeyi Wen, Jiashuai Shi, Qinbin Li, Bingsheng He, Jian Chen:
ThunderSVM: A Fast SVM Library on GPUs and CPUs. J. Mach. Learn. Res. 19: 21:1-21:5 (2018)
Coauthor Index
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