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2020 – today
- 2025
[c19]Mengyang Wu, Yuzhi Zhao, Jialun Cao, Mingjie Xu, Zhongming Jiang, Xuehui Wang, Qinbin Li, Guangneng Hu, Shengchao Qin, Chi-Wing Fu:
ICM-Assistant: Instruction-tuning Multimodal Large Language Models for Rule-based Explainable Image Content Moderation. AAAI 2025: 8413-8422- [i22]Zhaomin Wu, Zhen Qin, Junyi Hou, Haodong Zhao, Qinbin Li, Bingsheng He, Lixin Fan:
Vertical Federated Learning in Practice: The Good, the Bad, and the Ugly. CoRR abs/2502.08160 (2025) - 2024
- [j10]Yiqun Diao, Yutong Yang, Qinbin Li, Bingsheng He, Mian Lu:
OEBench: Investigating Open Environment Challenges in Real-World Relational Data Streams. Proc. VLDB Endow. 17(6): 1283-1296 (2024) - [j9]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:
LLM-PBE: Assessing Data Privacy in Large Language Models. Proc. VLDB Endow. 17(11): 3201-3214 (2024) - [j8]Zhaomin Wu
, Qinbin Li, Bingsheng He:
Practical Vertical Federated Learning With Unsupervised Representation Learning. IEEE Trans. Big Data 10(6): 864-878 (2024) - [c18]Yiqun Diao, Qinbin Li, Bingsheng He:
Exploiting Label Skews in Federated Learning with Model Concatenation. AAAI 2024: 11784-11792 - [c17]Qinbin Li, Chulin Xie, Xiaojun Xu, Xiaoyuan Liu, Ce Zhang, Bo Li, Bingsheng He, Dawn Song:
Effective and Efficient Federated Tree Learning on Hybrid Data. ICLR 2024 - [c16]Myeongseob Ko, Henry Li, Zhun Wang, Jonathan Patsenker, Jiachen T. Wang, Qinbin Li, Ming Jin, Dawn Song, Ruoxi Jia:
Boosting Alignment for Post-Unlearning Text-to-Image Generative Models. NeurIPS 2024 - [c15]Chulin Xie, Pin-Yu Chen, Qinbin Li, Arash Nourian, Ce Zhang, Bo Li:
Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM. SaTML 2024: 443-471 - [c14]Yuzheng Hu, Fan Wu, Qinbin Li, Yunhui Long, Gonzalo Munilla Garrido, Chang Ge, Bolin Ding, David A. Forsyth, Bo Li, Dawn Song:
SoK: Privacy-Preserving Data Synthesis. SP 2024: 4696-4713 - [c13]Moming Duan, Qinbin Li, Bingsheng He:
ModelGo: A Practical Tool for Machine Learning License Analysis. WWW 2024: 1158-1169 - [i21]Lixu Wang, Yang Zhao, Jiahua Dong, Ating Yin, Qinbin Li, Xiao Wang, Dusit Niyato, Qi Zhu:
Federated Learning with New Knowledge: Fundamentals, Advances, and Futures. CoRR abs/2402.02268 (2024) - [i20]Zhen Xiang, Linzhi Zheng, Yanjie Li, Junyuan Hong, Qinbin Li, Han Xie, Jiawei Zhang, Zidi Xiong, Chulin Xie, Carl Yang, Dawn Song, Bo Li:
GuardAgent: Safeguard LLM Agents by a Guard Agent via Knowledge-Enabled Reasoning. CoRR abs/2406.09187 (2024) - [i19]Qian Wang, Tianyu Wang, Qinbin Li, Jingsheng Liang, Bingsheng He:
MegaAgent: A Practical Framework for Autonomous Cooperation in Large-Scale LLM Agent Systems. CoRR abs/2408.09955 (2024) - [i18]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:
LLM-PBE: Assessing Data Privacy in Large Language Models. CoRR abs/2408.12787 (2024) - [i17]Myeongseob Ko, Henry Li, Zhun Wang, Jonathan Patsenker, Jiachen T. Wang, Qinbin Li, Ming Jin, Dawn Song, Ruoxi Jia:
Boosting Alignment for Post-Unlearning Text-to-Image Generative Models. CoRR abs/2412.07808 (2024) - [i16]Mengyang Wu, Yuzhi Zhao, Jialun Cao, Mingjie Xu, Zhongming Jiang, Xuehui Wang, Qinbin Li, Guangneng Hu, Shengchao Qin, Chi-Wing Fu:
ICM-Assistant: Instruction-tuning Multimodal Large Language Models for Rule-based Explainable Image Content Moderation. CoRR abs/2412.18216 (2024) - 2023
- [j7]Zhaomin Wu, Junhui Zhu, Qinbin Li, Bingsheng He:
DeltaBoost: Gradient Boosting Decision Trees with Efficient Machine Unlearning. Proc. ACM Manag. Data 1(2): 168:1-168:26 (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) - [c12]Chulin Xie, Yunhui Long, Pin-Yu Chen, Qinbin Li, Sanmi Koyejo, Bo Li:
Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks. CCS 2023: 1511-1525 - [c11]Yiqun Diao, Qinbin Li, Bingsheng He:
Towards Addressing Label Skews in One-Shot Federated Learning. ICLR 2023 - [c10]Qinbin Li, Bingsheng He, Dawn Song:
Adversarial Collaborative Learning on Non-IID Features. ICML 2023: 19504-19526 - [c9]Sixu Hu, Qinbin Li, Bingsheng He:
Communication-Efficient Generalized Neuron Matching for Federated Learning. ICPP 2023: 254-263 - [c8]Qinbin Li, Zhaomin Wu, Yanzheng Cai, Yuxuan Han, Ching Man Yung, Tianyuan Fu, Bingsheng He:
FedTree: A Federated Learning System For Trees. MLSys 2023 - [i15]Yuzheng Hu, Fan Wu, Qinbin Li, Yunhui Long, Gonzalo Munilla Garrido, Chang Ge, Bolin Ding, David A. Forsyth, Bo Li, Dawn Song:
SoK: Privacy-Preserving Data Synthesis. CoRR abs/2307.02106 (2023) - [i14]Yiqun Diao, Yutong Yang, Qinbin Li, Bingsheng He, Mian Lu:
OEBench: Investigating Open Environment Challenges in Real-World Relational Data Streams. CoRR abs/2308.15059 (2023) - [i13]Qinbin Li, Chulin Xie, Xiaojun Xu, Xiaoyuan Liu, Ce Zhang, Bo Li, Bingsheng He, Dawn Song:
Effective and Efficient Federated Tree Learning on Hybrid Data. CoRR abs/2310.11865 (2023) - [i12]Yiqun Diao, Qinbin Li, Bingsheng He:
Exploiting Label Skews in Federated Learning with Model Concatenation. CoRR abs/2312.06290 (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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