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2020 – today
- 2024
[j3]Junlin Wei
, Pengfei Lin, Jinrong Jiang, Hailong Liu, Lian Zhao, Yehong Zhang, Xiang Han, Feng Zhang, Jian Huang, Yuzhu Wang, Youyun Li, Yue Yu, Xuebin Chi:
Accelerating LASG/IAP climate system ocean model version 3 for performance portability using Kokkos. Future Gener. Comput. Syst. 160: 901-917 (2024)- [j2]Shiyu Liu, Jinglong Luo, Yehong Zhang, Hui Wang, Yue Yu, Zenglin Xu:
Efficient privacy-preserving Gaussian process via secure multi-party computation. J. Syst. Archit. 151: 103134 (2024) - [c12]Xin Mu, Yu Wang, Zhengan Huang, Junzuo Lai, Yehong Zhang, Hui Wang, Yue Yu:
EncryIP: A Practical Encryption-Based Framework for Model Intellectual Property Protection. AAAI 2024: 21438-21445 - [c11]Jinglong Luo, Yehong Zhang, Zhuo Zhang, Jiaqi Zhang, Xin Mu, Hui Wang, Yue Yu, Zenglin Xu:
SecFormer: Fast and Accurate Privacy-Preserving Inference for Transformer Models via SMPC. ACL (Findings) 2024: 13333-13348 - [c10]Xin Mu, Yu Wang, Yehong Zhang, Jiaqi Zhang, Hui Wang, Yang Xiang, Yue Yu:
Model Provenance via Model DNA. ECAI 2024: 1043-1050 - [c9]Shiyu Liu, Wei Shi, Zenglin Xu, Shaogao Lv, Yehong Zhang, Hui Wang:
Meta-Learning via PAC-Bayesian with Data-Dependent Prior: Generalization Bounds from Local Entropy. IJCAI 2024: 4578-4586 - [i13]Jinglong Luo, Yehong Zhang, Jiaqi Zhang, Xin Mu, Hui Wang, Yue Yu, Zenglin Xu:
SecFormer: Towards Fast and Accurate Privacy-Preserving Inference for Large Language Models. CoRR abs/2401.00793 (2024) - [i12]Han Zhang, Lin Gui, Yu Lei, Yuanzhao Zhai, Yehong Zhang, Yulan He, Hui Wang, Yue Yu, Kam-Fai Wong, Bin Liang, Ruifeng Xu:
COPR: Continual Human Preference Learning via Optimal Policy Regularization. CoRR abs/2402.14228 (2024) - [i11]Rachael Hwee Ling Sim, Yehong Zhang, Trong Nghia Hoang, Xinyi Xu, Bryan Kian Hsiang Low, Patrick Jaillet:
Incentives in Private Collaborative Machine Learning. CoRR abs/2404.01676 (2024) - 2023
- [j1]Mohit Rajpal, Yehong Zhang, Bryan Kian Hsiang Low:
Pruning during training by network efficacy modeling. Mach. Learn. 112(7): 2653-2684 (2023) - [c8]Rachael Hwee Ling Sim, Yehong Zhang, Nghia Hoang, Xinyi Xu, Bryan Kian Hsiang Low, Patrick Jaillet:
Incentives in Private Collaborative Machine Learning. NeurIPS 2023 - [c7]Jinglong Luo, Yehong Zhang, Jiaqi Zhang, Shuang Qin, Hui Wang, Yue Yu, Zenglin Xu:
Practical privacy-preserving Gaussian process regression via secret sharing. UAI 2023: 1315-1325 - [i10]Jinglong Luo, Yehong Zhang, Jiaqi Zhang, Shuang Qin, Hui Wang, Yue Yu, Zenglin Xu:
Practical Privacy-Preserving Gaussian Process Regression via Secret Sharing. CoRR abs/2306.14498 (2023) - [i9]Mohit Rajpal, Lac Gia Tran, Yehong Zhang, Bryan Kian Hsiang Low:
Hessian-Aware Bayesian Optimization for Decision Making Systems. CoRR abs/2308.00629 (2023) - [i8]Xin Mu, Yu Wang, Yehong Zhang, Jiaqi Zhang, Hui Wang, Yang Xiang, Yue Yu:
Model Provenance via Model DNA. CoRR abs/2308.02121 (2023) - [i7]Yehong Zhang, Jun Wu, Hui Xu:
Fuzz Driver Synthesis for Rust Generic APIs. CoRR abs/2312.10676 (2023) - [i6]Xin Mu, Yu Wang, Zhengan Huang, Junzuo Lai, Yehong Zhang, Hui Wang, Yue Yu:
EncryIP: A Practical Encryption-Based Framework for Model Intellectual Property Protection. CoRR abs/2312.12049 (2023) - 2021
- [c6]Rachael Hwee Ling Sim, Yehong Zhang, Bryan Kian Hsiang Low, Patrick Jaillet:
Collaborative Bayesian Optimization with Fair Regret. ICML 2021: 9691-9701 - [i5]Wei Zeng, Xiaozhe Ren, Teng Su, Hui Wang, Yi Liao, Zhiwei Wang, Xin Jiang, ZhenZhang Yang, Kaisheng Wang, Xiaoda Zhang, Chen Li, Ziyan Gong, Yifan Yao, Xinjing Huang, Jun Wang, Jianfeng Yu, Qi Guo, Yue Yu, Yan Zhang, Jin Wang, Hengtao Tao, Dasen Yan, Zexuan Yi, Fang Peng, Fangqing Jiang, Han Zhang, Lingfeng Deng, Yehong Zhang, Zhe Lin, Chao Zhang, Shaojie Zhang, Mingyue Guo, Shanzhi Gu, Gaojun Fan, Yaowei Wang, Xuefeng Jin, Qun Liu, Yonghong Tian:
PanGu-α: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation. CoRR abs/2104.12369 (2021) - 2020
- [c5]Tong Teng, Jie Chen, Yehong Zhang, Bryan Kian Hsiang Low:
Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression. AAAI 2020: 5997-6004 - [c4]Rachael Hwee Ling Sim, Yehong Zhang, Mun Choon Chan, Bryan Kian Hsiang Low:
Collaborative Machine Learning with Incentive-Aware Model Rewards. ICML 2020: 8927-8936 - [i4]Rachael Hwee Ling Sim, Yehong Zhang, Mun Choon Chan, Bryan Kian Hsiang Low:
Collaborative Machine Learning with Incentive-Aware Model Rewards. CoRR abs/2010.12797 (2020)
2010 – 2019
- 2019
- [c3]Yehong Zhang, Zhongxiang Dai, Bryan Kian Hsiang Low:
Bayesian Optimization with Binary Auxiliary Information. UAI 2019: 1222-1232 - [i3]Yehong Zhang, Zhongxiang Dai, Kian Hsiang Low:
Bayesian Optimization with Binary Auxiliary Information. CoRR abs/1906.07277 (2019) - [i2]Tong Teng, Jie Chen, Yehong Zhang, Kian Hsiang Low:
Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression. CoRR abs/1912.02641 (2019) - 2016
- [c2]Yehong Zhang, Trong Nghia Hoang, Kian Hsiang Low, Mohan S. Kankanhalli:
Near-Optimal Active Learning of Multi-Output Gaussian Processes. AAAI 2016: 2351-2357 - [c1]Yuhui Wang, Christian von der Weth, Yehong Zhang, Kian Hsiang Low, Vivek K. Singh, Mohan S. Kankanhalli:
Concept Based Hybrid Fusion of Multimodal Event Signals. ISM 2016: 14-19 - 2015
- [i1]Yehong Zhang, Trong Nghia Hoang, Kian Hsiang Low, Mohan S. Kankanhalli:
Near-Optimal Active Learning of Multi-Output Gaussian Processes. CoRR abs/1511.06891 (2015)
Coauthor Index
aka: Bryan Kian Hsiang Low
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last updated on 2024-10-28 21:14 CET by the dblp team
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