Yehong Zhang

According to our database, Yehong Zhang authored at least 16 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

COPR: Continual Human Preference Learning via Optimal Policy Regularization.

Han Zhang, Lin Gui, Yu Lei, Yuanzhao Zhai, Yehong Zhang, Yulan He, Hui Wang, Yue Yu, Kam-Fai Wong, Bin Liang, Ruifeng Xu

CoRR, 2024

SecFormer: Towards Fast and Accurate Privacy-Preserving Inference for Large Language Models.

Jinglong Luo, Yehong Zhang, Jiaqi Zhang, Xin Mu, Hui Wang, Yue Yu, Zenglin Xu

CoRR, 2024

EncryIP: A Practical Encryption-Based Framework for Model Intellectual Property Protection.

Xin Mu, Yu Wang, Zhengan Huang, Junzuo Lai, Yehong Zhang, Hui Wang, Yue Yu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Pruning during training by network efficacy modeling.

Mohit Rajpal, Yehong Zhang, Bryan Kian Hsiang Low

Mach. Learn., July, 2023

Fuzz Driver Synthesis for Rust Generic APIs.

Yehong Zhang, Jun Wu, Hui Xu

CoRR, 2023

Model Provenance via Model DNA.

Xin Mu, Yu Wang, Yehong Zhang, Jiaqi Zhang, Hui Wang, Yang Xiang, Yue Yu

CoRR, 2023

Hessian-Aware Bayesian Optimization for Decision Making Systems.

Mohit Rajpal, Lac Gia Tran, Yehong Zhang, Bryan Kian Hsiang Low

CoRR, 2023

Practical privacy-preserving Gaussian process regression via secret sharing.

Jinglong Luo, Yehong Zhang, Jiaqi Zhang, Shuang Qin, Hui Wang, Yue Yu, Zenglin Xu

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Incentives in Private Collaborative Machine Learning.

Rachael Hwee Ling Sim, Yehong Zhang, Nghia Hoang, Xinyi Xu, Bryan Kian Hsiang Low, Patrick Jaillet

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2021

PanGu-α: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation.

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

CoRR, 2021

Collaborative Bayesian Optimization with Fair Regret.

Rachael Hwee Ling Sim, Yehong Zhang, Bryan Kian Hsiang Low, Patrick Jaillet

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Collaborative Machine Learning with Incentive-Aware Model Rewards.

Rachael Hwee Ling Sim, Yehong Zhang, Mun Choon Chan, Bryan Kian Hsiang Low

Proceedings of the 37th International Conference on Machine Learning, 2020

Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression.

Tong Teng, Jie Chen, Yehong Zhang, Bryan Kian Hsiang Low

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Bayesian Optimization with Binary Auxiliary Information.

Yehong Zhang, Zhongxiang Dai, Bryan Kian Hsiang Low

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

2016

Concept Based Hybrid Fusion of Multimodal Event Signals.

Yuhui Wang, Christian von der Weth, Yehong Zhang, Kian Hsiang Low, Vivek K. Singh, Mohan S. Kankanhalli

Proceedings of the IEEE International Symposium on Multimedia, 2016

Near-Optimal Active Learning of Multi-Output Gaussian Processes.

Yehong Zhang, Trong Nghia Hoang, Kian Hsiang Low, Mohan S. Kankanhalli

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016